AI Engineer/ML Engineer - Senior Developers - AI Training - Las Vegas, US

🏢 Summary: Opportunity to join an expert network to train and evaluate advanced large language models by reviewing architectures, auditing ML code, and refining RLHF workflows. The role involves applying deep machine learning expertise to assess model reasoning, benchmark performance, and improve alignment. Work is task-based and remote, focused on high-level technical evaluation of AI systems. 🗂️ Requirements: BS/MS/PhD in Computer Science, AI, Robotics, or related quantitative field, Professional experience building, deploying, or fine-tuning ML models in production, Strong knowledge of neural networks (Transformers, CNNs, RNNs) and optimization techniques, Hands-on experience with Prompt Engineering, RLHF, or RAG workflows, Ability to audit ML code, training loops, and data preprocessing pipelines, Experience evaluating model reasoning, hallucinations, and biased outputs, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python for ML and data analysis 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, HuggingFace, RLHF, RAG, LangChain, AWS, SageMaker, GCP, VertexAI, Weights&Biases, Pinecone, Milvus, Weaviate, CNN, RNN 🏢 Description: AI & Machine Learning Engineer - AI Training About Prolific Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for AI and Machine Learning Engineers to join our Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll bring Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning. Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment. Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques. LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows. Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms. Analytical Critique: high attention to detail in spotting "hallucinations," biased outputs, or logical failures in AI-generated technical content. What you'll be doing in the role Evaluate LLM Architecture Logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy. Audit Code & Notebooks: validate ML-specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness. Refine RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness. Analyze Model Reasoning: critically assess how an AI model navigates complex chain-of-thought (CoT) prompts and identify where the reasoning breaks down. Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics. Key Technologies Frameworks: expert proficiency in PyTorch or TensorFlow/Keras. Language & Data: advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers. Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence the AI models of the future using professional legal expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home. We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity. Links to more information on Prolific Website Youtube Privacy Statement By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.

🏢 Summary: Paid opportunity to train and evaluate advanced large language models by auditing model logic, reviewing ML code, and refining RLHF workflows. The role involves applying deep machine learning expertise to assess, benchmark, and improve AI systems. Work is task-based with flexible hours and competitive hourly compensation. 🗂️ Requirements: BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or related quantitative field, Experience building, deploying, or fine-tuning ML models in production, Professional understanding of neural network architectures (Transformers, CNNs, RNNs), Hands-on experience with Prompt Engineering, RLHF, or RAG workflows, Ability to audit model logic and evaluate mathematical foundations of ML algorithms, Experience reviewing ML code, training loops, and data preprocessing pipelines, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python programming for ML tasks, Experience with cloud ML platforms (AWS SageMaker or Google Vertex AI), Familiarity with vector databases for RAG systems 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, HuggingFace, AWS, SageMaker, GoogleCloud, VertexAI, Weights&Biases, LangChain, Pinecone, Milvus, Weaviate, RLHF, RAG, CNN, RNN 🏢 Description: AI & Machine Learning Engineer - AI Training About Prolific Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for AI and Machine Learning Engineers to join our Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll bring Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning. Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment. Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques. LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows. Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms. Analytical Critique: high attention to detail in spotting "hallucinations," biased outputs, or logical failures in AI-generated technical content. What you'll be doing in the role Evaluate LLM Architecture Logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy. Audit Code & Notebooks: validate ML-specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness. Refine RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness. Analyze Model Reasoning: critically assess how an AI model navigates complex chain-of-thought (CoT) prompts and identify where the reasoning breaks down. Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics. Key Technologies Frameworks: expert proficiency in PyTorch or TensorFlow/Keras. Language & Data: advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers. Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence the AI models of the future using professional legal expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home. We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity. Links to more information on Prolific Website Youtube Privacy Statement By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.

🏢 Summary: Opportunity for an AI & Machine Learning Engineer to join an expert network and get paid to train, evaluate, and benchmark large language models. The role involves reviewing model architectures, auditing ML code, refining RLHF workflows, and assessing LLM reasoning quality. Work is task-based with flexible hours, focused on improving next-generation AI systems. 🗂️ Requirements: BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or related quantitative field with ML focus, Experience building, deploying, or fine-tuning ML models in production, Professional understanding of neural network architectures (Transformers, CNNs, RNNs), Hands-on experience with Prompt Engineering, RLHF, or RAG workflows, Ability to audit model logic, detect data contamination, and evaluate ML algorithms, Experience reviewing ML code, training loops, and model evaluations, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python programming for ML and data analysis, Experience with cloud ML platforms (AWS SageMaker or Google Vertex AI), Familiarity with vector databases for RAG evaluation 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, HuggingFace, RLHF, RAG, LangChain, SageMaker, VertexAI, AWS, GCP, Pinecone, Milvus, Weaviate, CNN, RNN 🏢 Description: AI & Machine Learning Engineer - AI Training About Prolific Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for AI and Machine Learning Engineers to join our Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll bring Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning. Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment. Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques. LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows. Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms. Analytical Critique: high attention to detail in spotting "hallucinations," biased outputs, or logical failures in AI-generated technical content. What you'll be doing in the role Evaluate LLM Architecture Logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy. Audit Code & Notebooks: validate ML-specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness. Refine RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness. Analyze Model Reasoning: critically assess how an AI model navigates complex chain-of-thought (CoT) prompts and identify where the reasoning breaks down. Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics. Key Technologies Frameworks: expert proficiency in PyTorch or TensorFlow/Keras. Language & Data: advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers. Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence the AI models of the future using professional legal expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home. We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity. Links to more information on Prolific Website Youtube Privacy Statement By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.

🏢 Summary: Opportunity for AI and Machine Learning Engineers to train and evaluate advanced LLMs by auditing model logic, refining RLHF workflows, and benchmarking model performance. The role involves reviewing ML code, assessing reasoning quality, and providing expert human feedback to improve AI systems. It is a paid, task-based position requiring deep technical expertise in ML and LLMs. 🗂️ Requirements: BS/MS/PhD in Computer Science, Artificial Intelligence, Robotics, or related quantitative field, Experience building, deploying, or fine-tuning ML models in production, Professional knowledge of neural network architectures (Transformers, CNNs, RNNs), Hands-on experience with Prompt Engineering, RLHF, or RAG workflows, Ability to audit ML code, model logic, and training data quality, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python programming for ML (NumPy, Pandas, Scikit-learn), Experience with cloud ML platforms (AWS SageMaker or Google Vertex AI) 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, CNN, RNN, RLHF, RAG, HuggingFace, AWS, SageMaker, GCP, VertexAI, Weights&Biases, LangChain, Pinecone, Milvus, Weaviate 🏢 Description: AI & Machine Learning Engineer - AI Training About Prolific Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for AI and Machine Learning Engineers to join our Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll bring Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning. Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment. Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques. LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows. Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms. Analytical Critique: high attention to detail in spotting "hallucinations," biased outputs, or logical failures in AI-generated technical content. What you'll be doing in the role Evaluate LLM Architecture Logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy. Audit Code & Notebooks: validate ML-specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness. Refine RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness. Analyze Model Reasoning: critically assess how an AI model navigates complex chain-of-thought (CoT) prompts and identify where the reasoning breaks down. Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics. Key Technologies Frameworks: expert proficiency in PyTorch or TensorFlow/Keras. Language & Data: advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers. Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence the AI models of the future using professional legal expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home. We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity. Links to more information on Prolific Website Youtube Privacy Statement By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.

🏢 Summary: Paid opportunity to train and evaluate large language models by reviewing model logic, auditing ML code, and providing expert feedback for RLHF and RAG workflows. The role involves technical assessment of AI outputs, benchmarking model performance, and refining model reasoning using deep machine learning expertise. Flexible, remote work with hourly compensation based on completed AI evaluation tasks. 🗂️ Requirements: BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or related quantitative field with focus on Machine Learning, Professional experience building, deploying, or fine-tuning ML models in production, Strong knowledge of neural network architectures (Transformers, CNNs, RNNs), Hands-on experience with Prompt Engineering, RLHF, or RAG workflows, Ability to audit ML code, training logic, and model evaluations, Experience evaluating model outputs for hallucinations, bias, and logical errors, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python programming for ML applications, Experience with cloud ML platforms (AWS SageMaker or Google Vertex AI), Familiarity with vector databases for RAG systems 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, HuggingFace, RLHF, RAG, LangChain, SageMaker, VertexAI, Pinecone, Milvus, Weaviate, CNN, RNN, Transformers 🏢 Description: AI & Machine Learning Engineer - AI Training About Prolific Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for AI and Machine Learning Engineers to join our Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll bring Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning. Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment. Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques. LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows. Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms. Analytical Critique: high attention to detail in spotting "hallucinations," biased outputs, or logical failures in AI-generated technical content. What you'll be doing in the role Evaluate LLM Architecture Logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy. Audit Code & Notebooks: validate ML-specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness. Refine RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness. Analyze Model Reasoning: critically assess how an AI model navigates complex chain-of-thought (CoT) prompts and identify where the reasoning breaks down. Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics. Key Technologies Frameworks: expert proficiency in PyTorch or TensorFlow/Keras. Language & Data: advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers. Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence the AI models of the future using professional legal expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home. We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity. Links to more information on Prolific Website Youtube Privacy Statement By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.

🏢 Summary: Opportunity for AI and Machine Learning Engineers to join an expert network and get paid to train and evaluate advanced large language models. The role involves auditing model logic, validating ML code, refining RLHF workflows, and benchmarking model performance. Work is task-based and requires deep technical expertise in modern ML and LLM systems. 🗂️ Requirements: BS/MS/PhD in Computer Science, Artificial Intelligence, Robotics or related quantitative field, Experience building, deploying or fine-tuning ML models in production, Professional understanding of neural network architectures (Transformers, CNNs, RNNs), Hands-on experience with Prompt Engineering, RLHF or RAG workflows, Ability to audit model logic and evaluate ML algorithms mathematically, Experience validating ML code, training loops and data preprocessing, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python programming for ML 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, HuggingFace, RLHF, RAG, LangChain, AWS, SageMaker, GCP, VertexAI, Weights&Biases, Pinecone, Milvus, Weaviate 🏢 Description: AI & Machine Learning Engineer - AI Training About Prolific Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for AI and Machine Learning Engineers to join our Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll bring Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning. Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment. Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques. LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows. Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms. Analytical Critique: high attention to detail in spotting "hallucinations," biased outputs, or logical failures in AI-generated technical content. What you'll be doing in the role Evaluate LLM Architecture Logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy. Audit Code & Notebooks: validate ML-specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness. Refine RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness. Analyze Model Reasoning: critically assess how an AI model navigates complex chain-of-thought (CoT) prompts and identify where the reasoning breaks down. Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics. Key Technologies Frameworks: expert proficiency in PyTorch or TensorFlow/Keras. Language & Data: advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers. Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence the AI models of the future using professional legal expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home. We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity. Links to more information on Prolific Website Youtube Privacy Statement By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.

🏢 Summary: Paid remote opportunity for AI and Machine Learning Engineers to train, evaluate, and refine large language models using advanced technical expertise. The role involves auditing model logic, validating ML code, improving RLHF workflows, and benchmarking LLM performance. Candidates complete technical assessments and, if successful, contribute to high-impact AI training tasks on an hourly basis. 🗂️ Requirements: BS, MS, or PhD in Computer Science, AI, Robotics, or related quantitative field, Experience building, deploying, or fine-tuning ML models in production, Professional understanding of neural networks (Transformers, CNNs, RNNs), Hands-on experience with Prompt Engineering, RLHF, or RAG workflows, Ability to audit model logic and evaluate ML algorithms mathematically, Experience validating ML code, training loops, and data preprocessing, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python with ML libraries, Experience with cloud ML platforms (AWS SageMaker or Google Vertex AI), Familiarity with vector databases for RAG evaluation 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, HuggingFace, RLHF, RAG, LangChain, AWS, SageMaker, GCP, VertexAI, Weights&Biases, Pinecone, Milvus, Weaviate, CNN, RNN 🏢 Description: AI & Machine Learning Engineer - AI Training About Prolific Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for AI and Machine Learning Engineers to join our Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll bring Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning. Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment. Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques. LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows. Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms. Analytical Critique: high attention to detail in spotting "hallucinations," biased outputs, or logical failures in AI-generated technical content. What you'll be doing in the role Evaluate LLM Architecture Logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy. Audit Code & Notebooks: validate ML-specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness. Refine RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness. Analyze Model Reasoning: critically assess how an AI model navigates complex chain-of-thought (CoT) prompts and identify where the reasoning breaks down. Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics. Key Technologies Frameworks: expert proficiency in PyTorch or TensorFlow/Keras. Language & Data: advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers. Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence the AI models of the future using professional legal expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home. We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity. Links to more information on Prolific Website Youtube Privacy Statement By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.

🏢 Summary: Opportunity for experienced AI and Machine Learning Engineers to train and evaluate large language models through technical auditing, RLHF refinement, and performance benchmarking on a flexible, paid basis. The role involves reviewing model logic, validating ML code, and assessing AI reasoning quality using advanced ML expertise. Participants complete paid AI evaluation tasks remotely with competitive hourly rates. 🗂️ Requirements: BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or related quantitative field, Experience building, deploying, or fine-tuning ML models in production, Professional-level knowledge of neural network architectures (Transformers, CNNs, RNNs), Hands-on experience with Prompt Engineering, RLHF, or RAG workflows, Ability to audit model logic and detect training data contamination, Experience evaluating ML algorithms and mathematical proofs, High attention to detail in identifying hallucinations and biased outputs, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python programming with ML libraries, Experience with cloud ML platforms or MLOps tools, Familiarity with vector databases for RAG evaluation 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, HuggingFace, RLHF, RAG, LangChain, AWS, SageMaker, GoogleCloud, VertexAI, Weights&Biases, Pinecone, Milvus, Weaviate, CNN, RNN 🏢 Description: AI & Machine Learning Engineer - AI Training About Prolific Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for AI and Machine Learning Engineers to join our Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll bring Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning. Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment. Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques. LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows. Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms. Analytical Critique: high attention to detail in spotting "hallucinations," biased outputs, or logical failures in AI-generated technical content. What you'll be doing in the role Evaluate LLM Architecture Logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy. Audit Code & Notebooks: validate ML-specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness. Refine RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness. Analyze Model Reasoning: critically assess how an AI model navigates complex chain-of-thought (CoT) prompts and identify where the reasoning breaks down. Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics. Key Technologies Frameworks: expert proficiency in PyTorch or TensorFlow/Keras. Language & Data: advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers. Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence the AI models of the future using professional legal expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home. We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity. Links to more information on Prolific Website Youtube Privacy Statement By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.

🏢 Summary: Paid remote opportunity to train and evaluate large language models by reviewing architecture logic, auditing ML code, refining RLHF workflows, and benchmarking model performance. The role involves applying deep machine learning expertise to assess, improve, and align advanced AI systems. Candidates complete technical assessments and work on structured AI evaluation tasks on an hourly basis. 🗂️ Requirements: BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or related quantitative field, Experience building, deploying, or fine-tuning ML models in production, Professional understanding of neural network architectures (Transformers, CNNs, RNNs), Hands-on experience with Prompt Engineering, RLHF, or RAG workflows, Ability to audit model logic, detect data contamination, and evaluate ML algorithms, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python with ML libraries, Experience with cloud ML platforms or MLOps tools, Familiarity with vector databases for RAG evaluation 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, HuggingFace, RLHF, RAG, LangChain, AWS, SageMaker, GCP, VertexAI, Weights&Biases, Pinecone, Milvus, Weaviate, CNN, RNN 🏢 Description: AI & Machine Learning Engineer - AI Training About Prolific Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for AI and Machine Learning Engineers to join our Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll bring Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning. Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment. Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques. LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows. Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms. Analytical Critique: high attention to detail in spotting "hallucinations," biased outputs, or logical failures in AI-generated technical content. What you'll be doing in the role Evaluate LLM Architecture Logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy. Audit Code & Notebooks: validate ML-specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness. Refine RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness. Analyze Model Reasoning: critically assess how an AI model navigates complex chain-of-thought (CoT) prompts and identify where the reasoning breaks down. Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics. Key Technologies Frameworks: expert proficiency in PyTorch or TensorFlow/Keras. Language & Data: advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers. Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence the AI models of the future using professional legal expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home. We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity. Links to more information on Prolific Website Youtube Privacy Statement By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.

🏢 Summary: Opportunity to join an expert network as an AI & Machine Learning Engineer to train, evaluate, and benchmark large language models using deep technical expertise. The role involves auditing model logic, reviewing ML code, refining RLHF workflows, and assessing LLM reasoning quality. Successful candidates complete paid AI evaluation tasks with flexible, remote engagement. 🗂️ Requirements: BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or related quantitative field with ML focus, Professional experience building, deploying, or fine-tuning ML models in production, Strong knowledge of neural network architectures (Transformers, CNNs, RNNs), Experience with Prompt Engineering, RLHF, or RAG workflows, Ability to audit model logic and validate mathematical foundations of ML algorithms, Experience reviewing and validating ML code and training pipelines, High attention to detail in evaluating LLM outputs and reasoning quality 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, HuggingFace, AWS, SageMaker, GCP, VertexAI, Weights&Biases, LangChain, Pinecone, Milvus, Weaviate, RLHF, RAG, CNN, RNN 🏢 Description: AI & Machine Learning Engineer - AI Training About Prolific Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills. The role We're looking for AI and Machine Learning Engineers to join our Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models. Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter. What you'll bring Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning. Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment. Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques. LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows. Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms. Analytical Critique: high attention to detail in spotting "hallucinations," biased outputs, or logical failures in AI-generated technical content. What you'll be doing in the role Evaluate LLM Architecture Logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy. Audit Code & Notebooks: validate ML-specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness. Refine RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness. Analyze Model Reasoning: critically assess how an AI model navigates complex chain-of-thought (CoT) prompts and identify where the reasoning breaks down. Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics. Key Technologies Frameworks: expert proficiency in PyTorch or TensorFlow/Keras. Language & Data: advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers. Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain. Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation. Why Prolific is a great platform to join as a Participant Joining our Expert Network will give you the chance to influence the AI models of the future using professional legal expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home. We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity. Links to more information on Prolific Website Youtube Privacy Statement By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.