AI Engineer/ML Engineer - Senior Developers - AI Training - USA

🏢 Summary: Opportunity to join an expert network as an AI & Machine Learning Engineer to train, evaluate, and improve large language models through technical audits, RLHF refinement, and benchmarking tasks. The role involves reviewing model architectures, validating ML code, and assessing reasoning quality using deep learning expertise. It is a paid, flexible engagement focused on advancing next-generation AI systems. 🗂️ 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 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 foundations, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python for ML and data processing, 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, GCP, VertexAI, LangChain, Weights&Biases, 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 to join an expert network to train and evaluate advanced large language models by auditing architectures, reviewing ML code, refining RLHF workflows, and benchmarking model performance. The role involves paid, task-based work requiring deep machine learning expertise and technical evaluation of AI systems. 🗂️ Requirements: BS/MS/PhD in Computer Science, AI, 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 model logic and evaluate ML algorithms mathematically, Experience reviewing ML code, training loops and data preprocessing, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python for ML and data processing, 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 to join an expert network to train and evaluate advanced large language models by reviewing architecture logic, auditing ML code, and providing RLHF feedback. The role involves benchmarking model performance and critically assessing AI reasoning using deep machine learning expertise. It is a paid, task-based position focused on improving and aligning state-of-the-art AI 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 knowledge of neural network architectures (Transformers, CNNs, RNNs), Hands-on experience with Prompt Engineering, RLHF, or RAG workflows, Ability to audit ML code, training loops, and data preprocessing pipelines, Experience evaluating model outputs for accuracy, bias, and logical consistency, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python programming for ML applications 📃 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.

🏢 Summary: Opportunity to join an expert network as an AI & Machine Learning Engineer, contributing to training and evaluation of advanced LLMs through technical audits, RLHF feedback, and model benchmarking on a flexible, paid task basis. 🗂️ 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 training data contamination, and evaluate ML mathematical foundations, Experience reviewing ML code, training loops, and data preprocessing pipelines, Expert proficiency in PyTorch or TensorFlow/Keras, Advanced Python programming for ML tasks 📃 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, 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 large language models through technical auditing, RLHF feedback, and performance benchmarking. The role involves reviewing model architectures, validating ML code, and assessing reasoning quality to improve next-generation AI systems. Work is task-based and requires deep ML expertise with flexible, paid participation. 🗂️ 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, Experience reviewing ML code, training loops, and data preprocessing, Strong ability to evaluate LLM outputs, reasoning, and hallucinations 📃 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, validating ML code, refining RLHF workflows, and assessing LLM reasoning and performance. Successful candidates complete paid AI training tasks with flexible, project-based engagement. 🗂️ 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 model logic and detect training data contamination, Experience evaluating mathematical foundations of ML algorithms, 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), Familiarity with vector databases for RAG evaluation 📃 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, flexible opportunity to train and evaluate advanced large language models using deep machine learning expertise. The role involves auditing model logic, validating ML code, refining RLHF workflows, and benchmarking model performance. Participants complete technical AI evaluation tasks and provide high-quality feedback to improve next-generation 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 model logic and detect training data contamination, Experience reviewing ML code, training loops, and data preprocessing pipelines, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python with ML libraries 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, HuggingFace, RLHF, RAG, LangChain, SageMaker, VertexAI, AWS, GCP, 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.