Contract AI/ML Engineer — Remote RLHF Training & Evaluation

prolificacademicltd; United States; Remote; USD 55,000 - 110,000; Full time

Benefits offered by this job

Flexible scheduling

Fully remote

Job summary

Prolific Academic Ltd invites experts to join a participant-based, paid contract role focused on machine learning. You will contribute to the training and evaluation of large language models, with a role based in Boston and a fully remote, flexible schedule.

You will review explanations, audit ML code, provide structured feedback for RLHF workflows, and assess reasoning in chain-of-thought prompts. Expect up to one hour per study, with tasks aligned to available studies.

Qualifications

• BS/MS/PhD in CS/AI/Robotics or related field with ML focus.
• Hands-on production experience building, deploying, or fine-tuning ML models.
• Strong understanding of neural networks including Transformers, CNNs, and RNNs; knowledge of optimization techniques.
• Experience with prompt engineering, RLHF, or retrieval-augmented generation (RAG).
• Ability to audit model logic, flag training-data issues, and evaluate ML proofs.

Responsibilities

• Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical correctness.
• Audit ML code, training loops, preprocessing scripts, and evaluation notebooks for efficiency and accuracy.
• Provide structured human feedback supporting RLHF workflows and model alignment.
• Assess how models handle chain-of-thought prompts and identify reasoning breakdowns.
• Benchmark model outputs against defined technical taxonomies and performance metrics.

Skills

ML model deployment

Transformer architectures

Prompt engineering

RLHF workflows

RAG workflows

PyTorch

TensorFlow

Python programming

Education

BS/MS/PhD in ML related field

Tools

Hugging Face Transformers

AWS SageMaker

LangChain

Pinecone

Milvus

Weaviate

Job description

Prolific Academic Ltd invites experts to join a participant-based, paid contract role focused on machine learning. You will contribute to the training and evaluation of large language models, with a role based in Boston and a fully remote, flexible schedule.

You will review explanations, audit ML code, provide structured feedback for RLHF workflows, and assess reasoning in chain-of-thought prompts. Expect up to one hour per study, with tasks aligned to available studies.