AI Engineer/ML Engineer - Senior Developers - AI Training - Fort Worth, US

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

Benefits offered by this job

Remote work

Flexible scheduling

Job summary

prolificacademicltd is seeking senior AI/ML engineers for a remote, task-based engagement focused on training and evaluating large language models. You will provide expert critique of model behavior, code, and reasoning to improve performance and safety.

Responsibilities include evaluating explanations, auditing code and training loops, giving RLHF feedback, analyzing chain-of-thought errors, and benchmarking outputs against technical criteria, with flexible scheduling and compensation up to $80

Qualifications

• BS/MS/PhD in Computer Science, AI, Robotics, or related quantitative ML discipline
• Production experience with ML models
• Understanding of neural architectures (Transformers, CNNs, RNNs) and optimization methods
• Hands-on with prompt engineering, RLHF, or retrieval-augmented generation workflows
• Ability to audit complex model logic and detect data contamination

Responsibilities

• Evaluate AI-generated explanations for technical accuracy
• Audit ML code, notebooks, training loops, and preprocessing pipelines
• Provide expert feedback to strengthen RLHF for safety and alignment
• Analyze chain-of-thought reasoning to identify failures
• Run structured benchmarking across model outputs against technical criteria

Skills

Deep learning expertise

Transformer models

Python programming

Prompt engineering

RLHF

Model evaluation

Education

PhD in CS/AI

Tools

PyTorch

TensorFlow/Keras

Hugging Face Transformers

NumPy/Pandas

Weaviate

Job description

Role overview

A remote expert network is hiring senior AI and ML engineers to contribute paid technical work that trains and evaluates large language models. The position is task-driven rather than full-time, focusing on deep technical critique of model behavior, code, and reasoning rather than ongoing product development.

Responsibilities

• Evaluate AI-generated explanations covering model architectures, loss functions, and backpropagation for technical accuracy
• Audit ML-specific code, notebooks, training loops, and preprocessing pipelines for correctness and efficiency
• Provide expert human feedback that strengthens RLHF processes for safety, intent alignment, and helpfulness
• Analyze chain-of-thought reasoning to identify where models fail or produce flawed logic
• Run structured benchmarking across model outputs based on technical taxonomies and performance criteria

Requirements

• BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative ML discipline
• Production experience building, deploying, or fine-tuning machine learning models
• Professional understanding of neural network architectures such as Transformers, CNNs, and RNNs, plus optimization methods
• Hands-on work with prompt engineering, RLHF, or retrieval-augmented generation workflows
• Ability to audit complex model logic, flag training data contamination, and evaluate mathematical proofs underpinning ML algorithms
• Meticulous attention to detail for catching hallucinations, bias, and reasoning failures

Nice to have

• Expert proficiency in PyTorch or TensorFlow/Keras
• Strong Python skills with NumPy, Pandas, Scikit-learn, and Hugging Face Transformers
• Familiarity with AWS SageMaker, Google Vertex AI, Weights and Biases, or LangChain
• Exposure to vector databases including Pinecone, Milvus, or Weaviate for RAG evaluation

Benefits and work setup

• Remote, task-based engagement with flexible scheduling
• Compensation up to roughly $80 per hour, with many studies completed in under an hour