Remote ML Engineer – AI Audit & RLHF Research

prolificacademicltd; United States; Remote; USD 91,000 - 129,000; Part time

Benefits offered by this job

Up to $80/hr for qualifying tasks

Fully remote scheduling

Flexible, task-based sessions

Job summary

prolificacademic ltd. is seeking experienced machine learning engineers for remote, task-based research roles that focus on auditing, evaluating, and refining AI outputs with deep technical judgment.

Engagement is flexible and intermittent, designed to fit alongside other commitments. You will work on focused assignments reviewing model explanations, auditing code and datasets, and contributing to RLHF-driven alignment efforts.

Qualifications

• Bachelor's, Master's or PhD in CS/AI/related quantitative field with ML focus.
• Professional experience building, deploying, or fine-tuning ML models in production.
• Strong command of neural network architectures (Transformers, CNNs, RNNs) and modern optimization.
• Hands-on with prompt engineering, RLHF, or retrieval-augmented generation pipelines.
• Sharp analytical eye for spotting biased outputs, data contamination, and faulty reasoning.
• Located in the Baltimore area.

Responsibilities

• Review AI-generated explanations of architectures, loss, and backpropagation for accuracy.
• Audit ML code, training scripts, and notebooks for correctness and efficiency.
• Provide structured human feedback to align models via RLHF workflows.
• Critically analyze chain-of-thought reasoning and surface failures or hallucinations.
• Run benchmarks across model outputs using defined metrics.

Skills

Neural networks

Prompt engineering

RLHF

Bias detection

Education

Bachelor's degree in CS/AI

Master's degree in ML/AI

PhD in ML/AI

Tools

PyTorch

TensorFlow

Keras

NumPy

Job description

prolificacademic ltd. is seeking experienced machine learning engineers for remote, task-based research roles that focus on auditing, evaluating, and refining AI outputs with deep technical judgment.

Engagement is flexible and intermittent, designed to fit alongside other commitments. You will work on focused assignments reviewing model explanations, auditing code and datasets, and contributing to RLHF-driven alignment efforts.