Senior AI/ML Engineer - LLM Training & Evaluation (Remote)

prolificacademicltd; United States; Remote; USD 69,000 - 110,000; Full time

Benefits offered by this job

Hourly pay up to $80

Fully remote

Flexible hours

Short skills onboarding

Job summary

Prolific Academic Ltd is seeking senior AI/ML engineers to join a fully remote expert contributor network. You’ll tackle paid tasks ranging from quick audits to hour-long sessions, contributing to training and evaluation of next‑gen language models.

Responsibilities include auditing training loops and notebooks, delivering high-quality feedback for RLHF, and assessing model reasoning. Flexible hours suited for experienced researchers with production ML experience.

Qualifications

• Degree in CS/AI/Robotics or related quantitative field with ML focus
• Production ML experience with deployment or fine-tuning
• Knowledge of transformer architectures and optimization techniques
• Hands-on experience with prompt engineering, RLHF, or RAG workflows
• Ability to audit model logic and detect data contamination
• Attention to detail for hallucinations and biases in AI content

Responsibilities

• Review explanations of model architectures, loss functions, and backpropagation for accuracy
• Audit ML code and notebooks for correctness and efficiency
• Provide high-quality human feedback to RLHF pipelines to improve alignment
• Assess chain-of-thought reasoning and identify logical breakdowns
• Run benchmarks across model outputs using defined metrics

Skills

Prompt engineering

RLHF

RAG workflows

Model evaluation

Education

Bachelor's / Master's / PhD in CS/AI/Robotics

Tools

PyTorch

TensorFlow/Keras

Hugging Face Transformers

AWS SageMaker / Vertex AI

LangChain / VectorDBs (Pinecone, Milvus, Weaviate)

Job description

Prolific Academic Ltd is seeking senior AI/ML engineers to join a fully remote expert contributor network. You’ll tackle paid tasks ranging from quick audits to hour-long sessions, contributing to training and evaluation of next‑gen language models.

Responsibilities include auditing training loops and notebooks, delivering high-quality feedback for RLHF, and assessing model reasoning. Flexible hours suited for experienced researchers with production ML experience.