AI Engineer/ML Engineer - Senior Developers - AI Training - Memphis, US

🏢 Summary: Opportunity for AI and Machine Learning Engineers to join an expert network and contribute to training and evaluating large language models through technical reviews, RLHF feedback, and model benchmarking. The role involves auditing ML code, analyzing AI reasoning, and evaluating model architectures while working flexibly on paid AI training tasks. Candidates with strong ML, deep learning, and LLM expertise can earn 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 Transformers, CNNs, RNNs, and optimization techniques, Hands-on experience with Prompt Engineering, RLHF, or RAG workflows, Ability to audit model logic and evaluate ML algorithms, Experience identifying hallucinations, bias, and logical failures in AI outputs, Expert proficiency in PyTorch or TensorFlow/Keras, Advanced Python skills with ML and data libraries, Experience with cloud ML or MLOps platforms, Familiarity with vector databases for RAG evaluation 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, HuggingFace, AWS, SageMaker, GoogleCloud, VertexAI, Weights&Biases, LangChain, Pinecone, Milvus, Weaviate, RLHF, RAG, CNNs, RNNs 🏢 Description: About Prolific Prolific is building a large pool of quality human data used by AI developers, researchers, and organizations 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, you'll complete a short assessment to evaluate your skills and suitability for AI tasks. Successful candidates will join as participants to help train and evaluate AI models through paid tasks. Researchers looking for these skills tend to pay up to $80 per hour. Tasks may require one hour of uninterrupted work, though many are shorter. What you'll bring - BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning - Experience building, deploying, or fine-tuning ML models in a production environment - Professional-level understanding of neural network architectures including Transformers, CNNs, and RNNs, as well as optimization techniques - Hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows - Ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms - 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 - Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy - Validate ML-specific code such as training loops, preprocessing scripts, and model evaluations for efficiency and correctness - Provide high-quality human feedback to improve alignment, safety, and helpfulness of AI models - Assess how AI models handle complex chain-of-thought prompts and identify reasoning failures - Conduct comparative testing between model outputs using technical taxonomies and performance metrics Key Technologies - PyTorch - TensorFlow - Keras - Python - NumPy - Pandas - Scikit-learn - Hugging Face Transformers - AWS SageMaker - Google Cloud Vertex AI - Weights & Biases - LangChain - Pinecone - Milvus - Weaviate Why join as a participant - Opportunity to influence future AI models using professional expertise - Competitive pay rates - Flexible hours - Remote work opportunities - Quick onboarding after passing the assessment By submitting your application, you agree that Prolific may collect and process personal data for recruiting and organizational planning purposes.

🏢 Summary: Opportunity for AI and Machine Learning Engineers to train and evaluate large language models through technical reviews, RLHF feedback, and model benchmarking tasks. The role involves auditing ML code and reasoning, assessing AI outputs, and contributing expertise in deep learning and LLM workflows on a flexible paid-task 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 Transformers, CNNs, RNNs, and optimization techniques, Hands-on experience with Prompt Engineering, RLHF, or RAG workflows, Ability to audit model logic and evaluate ML algorithms, Strong attention to detail in identifying hallucinations, bias, and logical failures, Expert proficiency in PyTorch or TensorFlow/Keras, Advanced Python skills with ML and data libraries, Experience with AWS SageMaker, Google Cloud Vertex AI, or MLOps tooling, Familiarity with vector databases for RAG evaluation 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, RLHF, RAG, AWS, SageMaker, VertexAI, LangChain, Pinecone, Milvus, Weaviate, CNNs, RNNs 🏢 Description: About Prolific Prolific is building a large pool of quality human data used by AI developers, researchers, and organizations to gather feedback and insights from paid study participants. The role We're looking for AI and Machine Learning Engineers to join the Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. Candidates complete a short assessment to evaluate suitability for AI tasks. Successful participants are invited to complete paid AI training and evaluation tasks. Researchers looking for these skills tend to pay up to $80 per hour. Tasks may require one hour of uninterrupted work, though many are shorter. What you'll bring - BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning - Experience building, deploying, or fine-tuning ML models in a production environment - Professional-level understanding of neural network architectures including Transformers, CNNs, and RNNs, as well as optimization techniques - Hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows - Ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms - 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 - Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy - Validate ML-specific code including training loops, preprocessing scripts, and model evaluations for efficiency and correctness - Provide high-quality human feedback to align models with human intent, safety, and helpfulness - Assess AI reasoning through complex chain-of-thought prompts and identify reasoning failures - Conduct comparative testing between model outputs using technical taxonomies and performance metrics Key Technologies - PyTorch or TensorFlow/Keras - Python with NumPy, Pandas, and Scikit-learn - Hugging Face Transformers - AWS SageMaker or Google Cloud Vertex AI - Weights & Biases and LangChain - Pinecone, Milvus, or Weaviate Why join as a participant - Competitive pay rates - Flexible hours - Remote work opportunities - Opportunity to contribute to the development of future AI systems By submitting your application, you agree that personal data may be collected for recruiting and organizational planning purposes as described in the Candidate Privacy Notice.

🏢 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 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, 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 opportunity for experienced AI/ML engineers to train and evaluate large language models by auditing architecture logic, code, and RLHF workflows. The role involves providing expert human feedback to improve model reasoning, safety, and performance. Work is task-based, remote, and focused on advanced LLM evaluation and optimization. 🗂️ Requirements: BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or related quantitative field, 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 mathematical foundations, 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, 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 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.

🏢 Summary: Opportunity to join an expert network to train and evaluate large language models by reviewing model logic, auditing ML code, and providing high-quality feedback for AI alignment. The role involves assessing LLM architectures, benchmarking outputs, and refining RLHF and RAG workflows. It offers paid, flexible, remote work for experienced ML professionals. 🗂️ 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 understanding of neural network architectures, Hands-on experience with Prompt Engineering, RLHF, or RAG workflows, Ability to audit model logic and evaluate mathematical foundations of ML algorithms, Experience validating ML code, training loops, and data preprocessing pipelines, High attention to detail in identifying hallucinations, bias, and logical errors in AI outputs 📃 Skills: Python, PyTorch, TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Transformers, HuggingFace, AWS, SageMaker, GoogleCloud, VertexAI, Weights&Biases, LangChain, Pinecone, Milvus, Weaviate, RLHF, RAG 🏢 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 audits, RLHF feedback, and model benchmarking tasks. The role involves assessing model architectures, reviewing ML code, and improving LLM reasoning quality. Work is task-based, remote, and focused on advancing next-generation AI systems. 🗂️ Requirements: BS/MS/PhD in Computer Science, Artificial Intelligence, Robotics, or related quantitative field, 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 ML code, training processes, and model logic, Experience evaluating model outputs for hallucinations, bias, and reasoning errors, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python programming for ML applications 📃 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, focused on training, evaluating, and refining large language models through technical audits, RLHF feedback, and model benchmarking tasks. The role involves assessing model architectures, validating ML code, and improving alignment and reasoning quality of advanced AI systems. It offers flexible, paid project-based work centered on cutting-edge LLM development. 🗂️ Requirements: BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or related quantitative field, 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 processes, and model logic, Proficiency in PyTorch or TensorFlow/Keras, Advanced Python programming for ML tasks, Experience with cloud ML platforms (AWS SageMaker, 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, 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.