LLM AI/ML Engineer — Train & Eval Next-Gen Models

Prolific; United States; Remote; USD 83,000 - 138,000; Full time

Benefits offered by this job

Flexible hours

Work from home

Competitive pay rates

Job summary

Prolific is seeking AI & Machine Learning Engineers to join its Expert Network to train and evaluate next-gen LLMs using deep technical expertise. You’ll complete a 10- to 15-minute test to assess fit, then potentially join Prolific as a participant with pay for AI tasks performed remotely.

You’ll evaluate model architectures, audit code and notebooks, and improve RLHF frameworks, with opportunities to work on cutting-edge prompts and RAG workflows. Competitive hourly pay and flexible hours.

Qualifications

• BS, MS or PhD in Computer Science, AI, Robotics, or related quantitative field with ML focus.
• Experience building, deploying, or fine-tuning ML models in production.

Responsibilities

• Review AI-generated explanations of architectures, losses, and backpropagation for accuracy.
• Validate ML code, training loops, data preprocessing, and evaluations for efficiency and correctness.
• Refine RLHF frameworks with high-quality human feedback.
• Assess model reasoning in chain-of-thought prompts and identify breakdowns.
• Conduct benchmark tests comparing model outputs using technical metrics.

Skills

Education focus

ML model evaluation

Deep learning mastery

LLM specialization

Code & notebook audit

Analytical critique

Education

BS/MS/PhD in CS/AI/related

Tools

PyTorch

TensorFlow/Keras

Python (NumPy, Pandas, sklearn)

Hugging Face Transformers

AWS SageMaker

Vertex AI

Weighs & Biases

LangChain

Pinecone/Milvus/Weaviate

Job description

Prolific is seeking AI & Machine Learning Engineers to join its Expert Network to train and evaluate next-gen LLMs using deep technical expertise. You’ll complete a 10- to 15-minute test to assess fit, then potentially join Prolific as a participant with pay for AI tasks performed remotely.

You’ll evaluate model architectures, audit code and notebooks, and improve RLHF frameworks, with opportunities to work on cutting-edge prompts and RAG workflows. Competitive hourly pay and flexible hours.