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

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

Benefits offered by this job

Remote work

Flexible scheduling

Competitive hourly pay

Paid expert network opportunities

Job summary

prolificacademicltd seeks experienced AI/ML engineers to join a paid expert network for evaluating and auditing language model behavior. This remote, task-based role emphasizes applying deep technical judgment to critique models rather than building production systems.

You will review explanations of architectures, audit training loops, provide feedback for alignment and safety, and help benchmark model reasoning with quantitative metrics and RLHF workflows. Flexible scheduling is offered.

Qualifications

• Advanced degree in CS/AI with ML focus.
• Hands-on experience deploying or fine-tuning ML models.
• Strong knowledge of Transformers, CNNs, RNNs and optimization.
• Experience with prompt engineering and RLHF or retrieval-augmented generation workflows.
• Ability to audit complex model logic and evaluate proofs behind ML algorithms.

Responsibilities

• Review explanations of model architectures for accuracy.
• Audit ML code, training loops, preprocessing, and evaluation pipelines.
• Provide high-quality human feedback to align models with human intent, safety, and helpfulness through RLHF workflows.
• Analyze reasoning in chain-of-thought prompts and pinpoint where logic breaks down.
• Run benchmarks between model outputs using technical taxonomies and quantitative metrics.

Skills

ML model development

Transformers

RLHF

Prompt engineering

Model evaluation

Education

MS/PhD in CS/AI/related field

BS in CS or related field

Tools

PyTorch

TensorFlow/Keras

Pandas

NumPy

Weights & Biases

LangChain

Pinecone/Milvus/Weaviate

Job description

Role overview

This opportunity invites experienced AI and machine learning engineers to join a paid expert network that supports the training and evaluation of large language models. Work is task-based and remote, focused on applying deep technical judgment to audit, critique, and improve model behavior rather than shipping production systems.

Responsibilities

• Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy
• Audit ML code and notebooks, including training loops, preprocessing scripts, and evaluation pipelines, for correctness and efficiency
• Supply high-quality human feedback used to align models with human intent, safety, and helpfulness through reinforcement learning workflows
• Analyze how models reason through complex chain-of-thought prompts and pinpoint where logic breaks down
• Run comparative benchmarks between model outputs using technical taxonomies and quantitative performance metrics

Requirements

• BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with an ML 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 optimization techniques
• Experience with prompt engineering, RLHF, or retrieval-augmented generation workflows
• Ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms
• Sharp attention to detail for catching hallucinations, biased outputs, and logical failures in AI-generated technical content

Nice to have

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

Benefits and work setup

• Remote, task-based work with flexible scheduling
• Compensation up to roughly $80 per hour for qualifying studies, with some tasks shorter than a full hour