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

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

Benefits dieser Stelle

Pay up to $80/hr

Fully remote with flexible scheduling

Quick onboarding

Zusammenfassung

Prolific Academic Ltd. is seeking senior AI and machine learning engineers for a paid participant opportunity in Nashville, focused on evaluating and critiquing model reasoning and code rather than shipping new systems.

The role emphasizes deep technical critique, prompt engineering, RLHF workflows, and dependencies on Transformers, CNNs, or RNNs with hands-on ML deployment experience. Fully remote-friendly, flexible scheduling, and paid assignments.

Qualifikationen

• Degree in CS/AI/Robotics or related quantitative discipline with ML focus.
• Production experience building, deploying, or fine-tuning ML models.
• Deep expertise in transformer/CNN/RNN architectures and optimization.
• Hands-on experience with prompt engineering, RLHF, or retrieval-augmented generation workflows.

Aufgaben

• Review AI-produced explanations of model architectures, loss functions, and backpropagation for technical accuracy.
• Validate ML code, including training loops, data preprocessing scripts, and evaluation notebooks.
• Provide structured human feedback to RLHF efforts to align models with user intent and safety.
• Identify and document failure modes where AI chain-of-thought reasoning collapses.
• Benchmark model outputs against taxonomies and quantitative metrics.

Kenntnisse

ML focus in degree

Production ML experience

Neural network architectures

Prompt engineering / RLHF / RAG

Ausbildung

BS/MS/PhD in CS/AI/Robotics

Tools

PyTorch

TensorFlow/Keras

Python (NumPy, Pandas, SciKit-learn)

Jobbeschreibung

Role overview

This is a paid participant opportunity for senior AI and machine learning engineers in Nashville who want to apply deep technical expertise to training and evaluating the next wave of large language models. The role is analytical and evaluation-driven, focused on critiquing model reasoning and code rather than shipping new ML systems. It is well suited to practitioners looking for flexible, remote-friendly expert work alongside their main careers.

Responsibilities

• Review AI-produced explanations of model architectures, loss functions, and backpropagation for technical accuracy.
• Validate ML code, including training loops, data preprocessing scripts, and evaluation notebooks, for correctness and efficiency.
• Supply structured human feedback that supports RLHF efforts to align models with user intent, safety, and helpfulness.
• Diagnose where AI chain-of-thought reasoning collapses and document those failure modes.
• Benchmark competing model outputs against established technical taxonomies and quantitative metrics.

Requirements

• BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a closely related quantitative discipline with an ML focus.
• Production experience building, deploying, or fine-tuning machine learning models.
• Deep expertise in neural network architectures such as Transformers, CNNs, RNNs, and their optimization regimes.
• Hands-on exposure to prompt engineering, RLHF, or retrieval-augmented generation (RAG) workflows.
• Sharp attention to detail for spotting hallucinations, biased outputs, contamination, or flawed proofs in AI-generated content.

Nice to have

• Advanced proficiency with PyTorch or TensorFlow/Keras, plus expert Python across NumPy, Pandas, and Scikit-learn.
• Familiarity with Hugging Face Transformers and vector databases such as Pinecone, Milvus, or Weaviate.
• Experience with cloud MLOps tooling like AWS SageMaker, Vertex AI, Weights & Biases, or LangChain.

Benefits and work setup

• Pay rates reaching up to $80 per hour for tasks that require this expertise.
• Fully remote with flexible scheduling and paid assignments generally under one uninterrupted hour.
• Quick onboarding once a brief technical assessment is passed.