AI Engineer/ML Engineer - Senior Developers - AI Training - Memphis, US

prolificacademicltd; United States; Remote; USD 66,000 - 110,000; Full time

Benefits offered by this job

Remote work

Flexible hours

Technical assessment

Job summary

prolificacademic ltd seeks a senior AI/ML engineer to evaluate frontier LLMs, audit training code, and critique model outputs. You will focus on deep technical judgment and error tracing rather than building models, working remotely with flexible hours in the US.

You will analyze prompts, assist in RLHF workflows, and benchmark reasoning quality using defined metrics and taxonomies. A strong ML background is required.

Qualifications

• BS, MS, or PhD in Computer Science, AI, Robotics, or a quantitative field with ML concentration.

Responsibilities

• Scrutinize AI explanations of architectures, loss functions, and backpropagation for accuracy.
• Audit ML code including training loops, data preprocessing, and evaluation notebooks for issues.
• Provide high-quality feedback for RLHF targeting alignment, safety, and helpfulness.
• Trace AI reasoning through chain-of-thought prompts to locate logical failures.
• Conduct benchmarks across model outputs using defined taxonomies and metrics.

Skills

Machine learning

Production ML

Code auditing

Analytical reasoning

Prompt engineering

RLHF

Retrieval augmented generation

Python

Neural networks

Education

Bachelor's/Master's/PhD in CS/AI/Robotics

Tools

PyTorch

TensorFlow/Keras

NumPy

Pandas

Scikit-learn

Hugging Face Transformers

Pinecone

Milvus

Weaviate

AWS SageMaker

Job description

Role overview

This is a paid participant opportunity for senior AI and machine learning engineers based in Memphis who want to channel their production ML experience into evaluating and refining frontier large language models. The role emphasizes deep technical judgment, code auditing, and analytical critique rather than model development. It suits engineers seeking flexible, remote-friendly work that fits alongside other commitments.

Responsibilities

• Scrutinize AI-generated explanations of architectures, loss functions, and backpropagation for accuracy.
• Audit ML code, including training loops, data preprocessing, and evaluation notebooks, flagging inefficiencies and bugs.
• Deliver high-quality feedback that fuels RLHF processes targeting intent alignment, safety, and helpfulness.
• Trace AI reasoning through chain-of-thought prompts to locate points of logical failure.
• Conduct comparative benchmarks across model outputs using defined taxonomies and quantitative metrics.

Requirements

• BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a quantitative field with a machine learning concentration.
• Professional experience building, deploying, or fine-tuning ML systems in production.
• Deep working knowledge of neural network architectures including Transformers, CNNs, RNNs, and associated optimization methods.
• Hands‑on involvement with prompt engineering, RLHF, or retrieval‑augmented generation workflows.
• Careful analytical eye for catching hallucinations, biased outputs, or mathematically unsound claims in AI-generated material.

Nice to have

• Expert command of PyTorch or TensorFlow/Keras, plus strong Python skills with NumPy, Pandas, and Scikit-learn.
• Experience with Hugging Face Transformers and vector stores such as Pinecone, Milvus, or Weaviate.
• Familiarity with cloud MLOps platforms such as AWS SageMaker, Vertex AI, Weights & Biases, or LangChain.

Benefits and work setup

• Hourly rates up to $80 depending on task complexity and researcher budget.
• Remote work with flexible hours and paid tasks typically under one uninterrupted hour.
• Streamlined onboarding following a short technical assessment.