Remote AI & ML Engineer — Train & Evaluate Next‑Gen LLMs

Prolific; United States; Remote; USD 83,000 - 110,000; Full time

Job summary

Prolific is seeking AI & Machine Learning Engineers to join our Expert Network, training and evaluating next-gen LLMs. You may complete paid tasks of varying lengths and earn up to $80 per hour, with remote work options and flexible hours.

Role focuses on evaluating architectures, auditing code/notebooks, and refining RLHF and CoT reasoning. Must hold a advanced degree in a quantitative field and have production ML experience.

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.
• Deep learning mastery across transformers, CNNs, RNNs and optimizers.
• Hands-on LLM specialization: Prompt Engineering, RLHF, or RAG workflows.
• Ability to audit model logic, data contamination and proofs behind ML algorithms.
• Attention to detail in spotting hallucinations, biases, or logical failures in AI content.

Responsibilities

• Evaluate LLM architecture logic for technical accuracy.
• Audit ML code and notebooks for efficiency and correctness.
• Refine RLHF frameworks with high-quality human feedback.
• Analyze model reasoning and break down chain-of-thought prompts.
• Benchmark performance across model outputs using technical metrics.

Skills

Production ML models

Model evaluation

ML model debugging

Analytical critique

Hallucination detection

CoT analysis

Education

BS/MS/PhD in CS/AI/Robotics or related quantitative field with ML focus

Tools

PyTorch

TensorFlow/Keras

Python (NumPy, Pandas, Scikit-learn)

Hugging Face Transformers

Weave/Weaviate or Vector DBs

Job description

Prolific is seeking AI & Machine Learning Engineers to join our Expert Network, training and evaluating next-gen LLMs. You may complete paid tasks of varying lengths and earn up to $80 per hour, with remote work options and flexible hours.

Role focuses on evaluating architectures, auditing code/notebooks, and refining RLHF and CoT reasoning. Must hold a advanced degree in a quantitative field and have production ML experience.