Remote AI & ML Engineer — Train & Evaluate LLMs

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

Job summary

Prolific is seeking AI and Machine Learning Engineers to join our Expert Network for training and evaluating next-gen LLMs. You will assess architectures, audit code, and improve RLHF workflows while earning competitive pay by working on meaningful AI tasks from home.

Qualified candidates will have ML-focused degrees and production ML experience, with mastery of deep learning, Transformers, and Python tooling. Remote work with flexible hours is available.

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 with neural networks (Transformers/CNNs/RNNs) and optimization.
• Hands-on experience with Prompt Engineering, RLHF or RAG workflows.
• Ability to audit complex model logic and evaluate proofs behind ML algorithms.

Responsibilities

• Evaluate LLM architecture logic by reviewing AI explanations for technical accuracy.
• Audit ML code and notebooks for efficiency and correctness.
• Refine RLHF frameworks to align models with human intent and safety.
• Analyze model reasoning and identify breakdowns in chain-of-thought prompts.
• Benchmark model outputs using technical taxonomies and performance metrics.

Skills

ML engineer

Deep learning

LLM

Prompt Engineering

RLHF

RAG

Python

PyTorch

TensorFlow

Code auditing

Model evaluation

Education

BS/MS/PhD in Computer Science/AI/Robotics

ML-focused quantitative field

Tools

PyTorch

TensorFlow/Keras

Python (NumPy/Pandas/Scikit-learn)

Hugging Face Transformers

AWS SageMaker

Google Vertex AI

Weights & Biases

LangChain

Pinecone/Milvus/Weaviate

Job description

Prolific is seeking AI and Machine Learning Engineers to join our Expert Network for training and evaluating next-gen LLMs. You will assess architectures, audit code, and improve RLHF workflows while earning competitive pay by working on meaningful AI tasks from home.

Qualified candidates will have ML-focused degrees and production ML experience, with mastery of deep learning, Transformers, and Python tooling. Remote work with flexible hours is available.