Senior AI Engineer: End-to-End RL & LLM Architect

EnableComp LLC; United States; Presencial; USD 150.000 - 210.000; Jornada completa

Descripción de la vacante

EnableComp LLC is seeking a Senior AI Engineer to design, train, and evaluate end-to-end machine learning systems. You will own experiments from data and environment design through training, evaluation, and results reporting, collaborating with domain experts and communicating findings to technical and non-technical audiences.

The role demands hands-on reinforcement learning with language models, strong Python and PyTorch skills, and fluency with the Hugging Face ecosystem.

Formación

• 3+ years of hands-on experience training or fine-tuning language models.
• Experience with policy optimization methods for language models (PPO/DPO/GRPO) and their failure modes.
• Strong Python and PyTorch skills; fluent in Hugging Face ecosystem.
• Experience building and evaluating LLM-based agents or multi-turn systems.
• Ability to translate complex documentation into precise, testable outputs.
• Experience with HIPAA data handling preferred.

Responsabilidades

• Collaborate with domain experts to capture knowledge and encode it structurally.
• Analyze datasets for quality and coverage; resolve issues with stakeholders.
• Design RL environments, reward functions, and verifiers.
• Train and fine-tune language models using supervised and RL methods.
• Run experiments with versioned configurations, tracking, and budgeting.
• Present findings to engineers, domain experts, and business leaders.
• Document results and next steps in clear technical write-ups.

Conocimientos

Python

PyTorch

Hugging Face

Reinforcement learning

Language model fine-tuning

Experiment tracking

Technical writing

Data analysis

Educación

Bachelor's degree in CS/ML

MS or PhD preferred

Herramientas

Hugging Face ecosystem

Knowledge graphs

Ontologies

Descripción del empleo

EnableComp LLC is seeking a Senior AI Engineer to design, train, and evaluate end-to-end machine learning systems. You will own experiments from data and environment design through training, evaluation, and results reporting, collaborating with domain experts and communicating findings to technical and non-technical audiences.

The role demands hands-on reinforcement learning with language models, strong Python and PyTorch skills, and fluency with the Hugging Face ecosystem.