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

prolificacademicltd; USA; Remote; USD 91.000 - 129.000; Teilzeit

Benefits dieser Stelle

Remote work

Flexible scheduling

Zusammenfassung

prolificacademicltd is seeking senior AI/ML engineers for remote, task-based technical work that trains and evaluates large language models. You will critique model behavior, code, and reasoning, focusing on deep technical feedback rather than ongoing product development.

Responsibilities include auditing training loops, evaluating explanations, and contributing to RLHF safety and alignment efforts. A strong foundation in neural networks and prompt engineering is essential.

Qualifikationen

• Advanced degree in a quantitative ML field or equivalent research experience.
• Production experience with ML models in training, deployment, or fine-tuning.
• Familiar with neural architectures (Transformers, CNNs, RNNs) and optimization methods.

Aufgaben

• Assess AI-generated explanations for architectural and mathematical accuracy.
• Audit ML code, notebooks, training loops, and preprocessing for correctness and efficiency.
• Provide expert feedback to strengthen RLHF processes for safety and helpfulness.
• Analyze chain-of-thought reasoning to identify failures or flawed logic.
• Benchmark model outputs against technical criteria.

Kenntnisse

Prompt engineering

RLHF

RAG workflows

Model evaluation

ML theory

Ausbildung

BS/MS/PhD in CS/AI/Robotics or related ML

Tools

PyTorch

TensorFlow/Keras

NumPy

Pandas

Scikit-learn

Hugging Face Transformers

Jobbeschreibung

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