Remote AI & ML Engineer for LLM Training | Flexible Hours

Prolific; United States; Remote; USD 66.000 - 110.000; Vollzeit

Zusammenfassung

Prolific seeks AI & Machine Learning Engineers to join its Expert Network, training and evaluating next‑gen LLMs with deep expertise. A quick 10–15 minute test precedes an invite to join as a paid participant for AI tasks.

Role focuses on evaluating architecture explanations, auditing training code, refining RLHF, and analyzing model reasoning, with flexible hours and work‑from‑home options.

Qualifikationen

• BS/MS/PhD in CS/AI/Robotics or related quantitative field with ML focus.
• Experience building, deploying, or fine-tuning ML models in production.
• Deep learning mastery: transformers, CNNs, RNNs; optimization techniques.
• LLM specialization: Prompt Engineering, RLHF, or RAG workflows.
• Technical rigor: audit model logic and data contamination; evaluate proofs.
• Analytical critique: detect hallucinations or biased outputs in AI content.

Aufgaben

• Evaluate LLM architecture logic 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 failure points in CoT prompts.
• Benchmark model outputs using defined technical metrics.

Kenntnisse

ML model development

LLM fundamentals

Prompt Engineering

RLHF

RAG workflows

Model evaluation & debugging

Analytical thinking

Code review

Ausbildung

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

AWS SageMaker

Google Cloud Vertex AI

Weights & Biases

LangChain

Pinecone / Milvus / Weaviate

Jobbeschreibung

Prolific seeks AI & Machine Learning Engineers to join its Expert Network, training and evaluating next‑gen LLMs with deep expertise. A quick 10–15 minute test precedes an invite to join as a paid participant for AI tasks.

Role focuses on evaluating architecture explanations, auditing training code, refining RLHF, and analyzing model reasoning, with flexible hours and work‑from‑home options.