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

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

Benefits offered by this job

Remote work

Flexible hours

Competitive hourly rates up to $80

Job summary

Prolific Academic Ltd invites experienced AI and ML engineers to contribute to training and evaluating next-generation large language models. Work is performed remotely as part of an expert network, with flexible paid engagements for independent professionals based in or near Milwaukee.

Responsibilities include reviewing explanations of model architectures and loss functions, auditing training loops and data preprocessing, and providing high-quality feedback for RLHF workflows to improve

Qualifications

• BS/MS/PhD in CS/AI with ML focus.
• Hands-on ML model development and deployment experience.
• Experience with Transformers, CNNs, and RNNs.
• Ability to audit model logic and identify data contamination.

Responsibilities

• Review explanations of model architectures, loss functions, and backpropagation for technical accuracy.
• Audit ML code and notebooks, including training loops and data preprocessing.
• Provide high-quality feedback for RLHF workflows to improve alignment with human intent.
• Evaluate chain-of-thought reasoning to identify breakdowns or flawed outputs.
• Benchmark model outputs against defined technical taxonomies and metrics.

Skills

Transformers

RNNs

CNNs

RLHF

Prompt engineering

Retrieval-augmented generation

Python

ML production deployment

Education

BS in Computer Science or related field

MS or PhD in CS/AI/related field

Tools

PyTorch

TensorFlow/Keras

Hugging Face Transformers

AWS SageMaker

LangChain

Pinecone

Milvus

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