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

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

Benefits dieser Stelle

Remote work

Flexible task-based work

Competitive hourly pay

Zusammenfassung

prolificacademicltd is offering a remote, paid expert network role for Senior machine learning engineers to audit, review, and provide structured feedback on LLM outputs and ML code. The position emphasizes methodological rigor and alignment with human expectations.

Responsibilities include auditing explanations, ensuring technical fidelity, and delivering high-quality judgments that improve RLHF safety and usefulness across model evaluations.

Qualifikationen

• BS/MS/PhD in CS/AI with ML focus.
• Experience deploying or fine-tuning ML models.
• Strong knowledge of transformers and optimization techniques.
• Hands-on prompt engineering and RLHF/RAG pipelines.
• Ability to critique model behavior, detect contamination, and assess mathematical underpinnings.

Aufgaben

• Critically review AI explanations of architectures, loss functions, and backpropagation for technical fidelity.
• Audit ML codebases and notebooks, including training loops and evaluation scripts, for correctness and performance.
• Deliver high-quality human judgments that drive RLHF alignment with respect to safety, helpfulness, and intent.
• Trace and critique chain-of-thought reasoning to surface breakdowns in model logic.
• Conduct systematic benchmark comparisons across model outputs using technical rubrics and metrics.

Kenntnisse

Audit ML code and models

RLHF alignment

Prompt engineering

Editorial accuracy

Ausbildung

Bachelor’s/Master’s/PhD in CS/AI/ML

Tools

PyTorch

TensorFlow/Keras

Hugging Face Transformers

LangChain

AWS SageMaker / Vertex AI

Jobbeschreibung

Role overview

Senior machine learning engineers are sought for a remote, paid expert network that supports the development and evaluation of large language models. The role emphasizes applied technical judgment: auditing AI-generated material, validating ML code, and producing structured feedback that helps align models with human expectations.

Responsibilities

• Critically review AI explanations of architectures, loss functions, and backpropagation for technical fidelity
• Audit ML codebases and notebooks, including training loops and evaluation scripts, for correctness and performance
• Deliver high-quality human judgments that drive RLHF alignment with respect to safety, helpfulness, and intent
• Trace and critique chain-of-thought reasoning to surface breakdowns in model logic
• Conduct systematic benchmark comparisons across model outputs using technical rubrics and metrics

Requirements

• BS, MS, or PhD in Computer Science, AI, Robotics, or a related quantitative field focused on machine learning
• Track record of building, deploying, or fine-tuning ML models in production settings
• Working command of neural network architectures (Transformers, CNNs, RNNs) and associated optimization techniques
• Hands-on experience with prompt engineering, RLHF, or RAG pipelines
• Ability to scrutinize complex model behavior, detect contamination, and assess mathematical underpinnings
• Strong editorial eye for hallucinations, bias, and logical inconsistencies

Nice to have

• Expert-level use of PyTorch or TensorFlow/Keras
• Advanced Python with NumPy, Pandas, Scikit-learn, and Hugging Face Transformers
• Familiarity with AWS SageMaker, Google Vertex AI, Weights & Biases, or LangChain
• Experience with vector stores like Pinecone, Milvus, or Weaviate for RAG evaluation

Benefits and work setup

• Remote, flexible task-based work
• Pay rates reaching up to about $80 per hour, with tasks designed to fit within roughly an hour of focused work