Senior AI Engineer: RL & LLM Expert for Impactful Systems

Carbon Data Solutions; United States; A distancia; USD 150.000 - 210.000; Jornada completa

Descripción de la vacante

EnableComp is seeking a Senior AI Engineer who will build, train, and evaluate machine learning models with a focus on reinforcement learning and language models. You will own experiments end-to-end—from data design to reporting—while collaborating with domain experts and communicating results to both technical and non-technical audiences.

The ideal candidate has hands-on RL experience, strong Python/PyTorch skills, and experience with Hugging Face and LM fine-tuning.

Formación

• Hands-on experience training or fine-tuning language models.
• Experience designing RL environments, reward functions, and verifiers.
• Experience with policy optimization methods for LMs (PPO, DPO, GRPO).
• Ability to analyze complex documentation and translate to structured, testable form.

Responsabilidades

• Capture domain knowledge and represent it in structured form.
• Analyze datasets for quality and coverage; coordinate with stakeholders.
• Perform exploratory and statistical analysis to inform modeling decisions.
• Create and curate training/evaluation datasets with automated and human validation.
• Design RL environments, reward functions, and verifiers.
• Train/fine-tune LMs using supervised and RL methods (PPO, DPO, GRPO).
• Establish baselines, run ablations, diagnose training issues.
• Follow literature and bring techniques into practice.
• Manage experiments with versioned configs, reproducible runs, tracking.
• Design/evaluate frameworks, metrics, benchmarks; compare models via AB testing.
• Document results and present findings to engineers and leadership.

Conocimientos

Reinforcement learning

Python

PyTorch

Language models

Experiment design

Educación

Bachelor’s degree in CS/ML/Stats (MS/PhD preferred)

Herramientas

Hugging Face

PyTorch

Python

Descripción del empleo

EnableComp is seeking a Senior AI Engineer who will build, train, and evaluate machine learning models with a focus on reinforcement learning and language models. You will own experiments end-to-end—from data design to reporting—while collaborating with domain experts and communicating results to both technical and non-technical audiences.

The ideal candidate has hands-on RL experience, strong Python/PyTorch skills, and experience with Hugging Face and LM fine-tuning.