AI Training & Evaluation Engineer - Remote, Up to $80/hr

Prolific; United States; Remote; USD 91,000 - 129,000; Full time

Benefits offered by this job

Competitive pay rates

Flexible hours

Work from home

Job summary

Prolific is seeking AI & ML Engineers to join our Expert Network to train and evaluate cutting-edge models. You will assess architecture, audit code, and refine RLHF/rag workflows, using PyTorch, TensorFlow, and Hugging Face. Expect up-front screening tests and flexible, paid collaboration.

Join a company defining the frontier of human data for AI. Ideal candidates have advanced degrees, hands-on ML production experience, and a deep mastery of DL architectures, prompting, and evaluation.

Qualifications

• BS/MS/PhD in CS/AI/Robotics with ML focus.
• Experience deploying or fine-tuning ML models in production.
• Deep learning mastery over Transformers/CNNs/RNNs.
• Hands-on LLM workflows: Prompt Engineering, RLHF, or RAG.
• Technical rigor: audit model logic and data contamination.
• Strong analytical critique: detect hallucinations and biases.

Responsibilities

• Evaluate LLM architecture logic and technical accuracy.
• Audit ML code/notebooks for efficiency and correctness.
• Refine RLHF frameworks to align models with human intent.
• Analyze model reasoning on chain-of-thought prompts.
• Benchmark model outputs against defined metrics.

Skills

Education: BS/MS/PhD

Model Training

DL Architectures

LLM Workflows

Model Auditing

Analytical Thinking

Education

BS/MS/PhD in CS/AI/Robotics

Tools

PyTorch

TensorFlow/Keras

NumPy

Pandas

Scikit-learn

Hugging Face Transformers

SageMaker

Vertex AI

Weights & Biases

LangChain

Pinecone

Milvus

Weaviate

Job description

Prolific is seeking AI & ML Engineers to join our Expert Network to train and evaluate cutting-edge models. You will assess architecture, audit code, and refine RLHF/rag workflows, using PyTorch, TensorFlow, and Hugging Face. Expect up-front screening tests and flexible, paid collaboration.

Join a company defining the frontier of human data for AI. Ideal candidates have advanced degrees, hands-on ML production experience, and a deep mastery of DL architectures, prompting, and evaluation.