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

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

Benefits offered by this job

Remote work

Competitive hourly rate up to $80

Flexible hours

Quick onboarding after skills test

Job summary

prolificacademicltd seeks experienced AI/ML engineers to join a remote expert network evaluating and refining next-generation language models. Earn by engaging in focused, paid tasks such as auditing training loops, prompts, and RLHF workflows from home, with flexible hours.

Applicants should have advanced degrees in CS/AI/Robotics and hands-on production ML experience, including transformers, optimization, and prompt engineering.

Qualifications

• BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or related quantitative field
• Hands-on experience building, deploying, or fine-tuning ML models in production
• Professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and modern optimization techniques
• Experience with prompt engineering, RLHF, or retrieval-augmented generation (RAG)
• Strong analytical rigor to audit complex model logic and evaluate proofs
• Attention to identify hallucinations, biased outputs, and logical failures in AI content

Responsibilities

• Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy
• Audit ML code and notebooks, including training loops and evaluation pipelines
• Provide high-quality human feedback used in RLHF workflows to align model behavior with human intent
• Critically evaluate chain-of-thought reasoning and identify breakdowns or flawed outputs
• Conduct benchmarking of model outputs against technical taxonomies and performance metrics

Skills

Hands-on ML model experience

Analytical rigor

Attention to detail

Audit complex model logic

Education

BS/MS/PhD in CS/AI/Robotics or related quantitative field

Tools

PyTorch

TensorFlow/Keras

NumPy

Pandas

Scikit-learn

Hugging Face Transformers

Job description

Role overview

This opportunity invites experienced AI and machine learning engineers to contribute to training and evaluating next-generation large language models. Work is performed remotely as part of an expert network, where participants apply deep technical knowledge to review, audit, and refine AI outputs. The arrangement suits independent professionals based in or near Milwaukee who want flexible, paid engagements focused on advancing model quality.

Responsibilities

• Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy
• Audit machine learning code and notebooks, including training loops, data preprocessing scripts, and evaluation pipelines
• Provide high-quality human feedback used in reinforcement learning from human feedback (RLHF) workflows to align model behavior with human intent
• Critically evaluate chain-of-thought reasoning, identifying where AI model logic breaks down or produces flawed outputs
• Conduct comparative benchmarking of model outputs against defined technical taxonomies and performance metrics

Requirements

• BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a machine learning focus
• Hands‑on experience building, deploying, or fine‑tuning ML models in production environments
• Professional‑level understanding of neural network architectures such as Transformers, CNNs, and RNNs, plus modern optimization techniques
• Practical experience with prompt engineering, RLHF, or retrieval‑augmented generation (RAG) workflows
• Strong analytical rigor with the ability to audit complex model logic, detect training data contamination, and evaluate mathematical proofs
• Attention to detail in identifying hallucinations, biased outputs, and logical failures in AI‑generated technical content

Nice to have

• Expert proficiency with PyTorch or TensorFlow/Keras
• Advanced Python skills including NumPy, Pandas, Scikit‑learn, and Hugging Face Transformers
• Familiarity with cloud MLOps tools such as AWS SageMaker, Google Cloud Vertex AI, Weights & Biases, or LangChain
• Experience with vector databases like Pinecone, Milvus, or Weaviate for RAG evaluation

Benefits and work setup

• Remote participation from home with flexible hours
• Competitive hourly rates up to $80 per hour, depending on the task
• Assignments typically require up to one hour of uninterrupted work, with many shorter engagements
• Quick onboarding after passing a short skills assessment