AI & ML Engineer: Train & Evaluate Next-Gen LLMs (Remote)

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

Job summary

Prolific seeks AI & Machine Learning Engineers to join our Expert Network for AI training and evaluation of next‑gen LLMs. A quick 10–15 minute test screens suitability, then paid tasks ranging up to $80/hour for one‑hour segments, with potential for flexible hours and remote work.

Ideal candidates hold a BS/MS/PhD in a quantitative field and have production ML experience, deep DL mastery, and hands‑on LLM work including RLHF or RAG. Strong Python and ML tooling skills are essential.

Qualifications

• Education aligned with CS/AI fields (BS/MS/PhD).
• Production experience building, deploying, or fine‑tuning ML models.
• Deep learning mastery over transformers, CNNs, RNNs.
• Hands‑on LLM work: Prompt Engineering, RLHF or RAG workflows.
• Ability to audit model logic and assess training data quality.

Responsibilities

• Evaluate LLM architecture logic and technical accuracy of explanations.
• Audit ML code/notebooks for efficiency and correctness.
• Refine RLHF frameworks to align models with human intent and safety.
• Analyze model reasoning and detect failure modes in CoT prompts.
• Benchmark model outputs using defined performance metrics.

Skills

ML model development

Deployment & fine-tuning

Prompt engineering

RLHF/RAG

LLM knowledge

Model evaluation

Education

BS/MS/PhD in CS/AI/Robotics

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 seeks AI & Machine Learning Engineers to join our Expert Network for AI training and evaluation of next‑gen LLMs. A quick 10–15 minute test screens suitability, then paid tasks ranging up to $80/hour for one‑hour segments, with potential for flexible hours and remote work.

Ideal candidates hold a BS/MS/PhD in a quantitative field and have production ML experience, deep DL mastery, and hands‑on LLM work including RLHF or RAG. Strong Python and ML tooling skills are essential.