AI Engineer

EnableComp

. Work with domain experts to capture specialized knowledge in structured, usable form .

Posted 10/13/2026full-timeRemote • Tennessee • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in training and fine-tuning language models using reinforcement learning methods, with a strong foundation in Python and PyTorch. Proficient in designing evaluation frameworks and ensuring compliance with HIPAA and data policies in a regulated environment.

Highest-signal resume keywords

Training Language ModelsReinforcement LearningPython ProgrammingPyTorch FrameworkHIPAA Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Language Model Fine-TuningStatistical AnalysisExploratory Data AnalysisAutomated GradingA/B TestingData ValidationReward Function DesignEvaluation Framework DesignTechnical WritingSynthetic Data Generation

Soft Skills

CollaborationClear CommunicationAdaptability

Tools & Technologies

Hugging Face EcosystemVersion Control SystemsExperiment Tracking Tools

Industry Keywords

Healthcare DataRegulated IndustryPHI HandlingKnowledge GraphsOntologies

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Work with domain experts to capture specialized knowledge in structured, usable form
Analyze source materials and datasets for quality, consistency, and coverage
Perform exploratory and statistical analysis to inform data, modeling, and evaluation decisions
Create and curate training and evaluation datasets using automated and human validation
Design reinforcement learning environments, reward functions, and verifiers
Train and fine-tune language models using supervised and reinforcement learning methods including PPO, DPO, and GRPO
Establish baselines, run ablations, and diagnose reward hacking, instability, and data leakage
Follow research literature and apply promising techniques
Manage versioned configurations, reproducible runs, experiment tracking, and compute budgeting
Design and extend evaluation frameworks, metrics, and benchmarks
Compare models and approaches through structured experiments and A/B testing
Document results, failures, and next steps in technical write-ups
Present findings to engineers, domain experts, and business leaders
Own experiments from design through code, training, and results
Collaborate closely with domain experts and adapt data, training, and evaluation approaches as knowledge evolves
Ensure all work complies with HIPAA and EnableComp data policies

Requirements

What you’ll need

Bachelor’s degree in computer science, machine learning, statistics, or a related field; MS or PhD preferred
Equivalent hands-on experience will be considered
3+ years of hands-on experience training or fine-tuning language models
Reinforcement learning experience, including designing an environment and reward function end to end and training a policy
Working knowledge of PPO, DPO, or GRPO and their failure modes
Strong Python and PyTorch skills
Fluency in the Hugging Face ecosystem and parameter-efficient fine-tuning techniques
Experience building and evaluating LLM-based agents or multi-turn systems
Experience designing language-model evaluations, including held-out sets and automated grading
Ability to analyze complex documentation and translate it into precise, structured, testable form
Clear technical writing
Comfort working with non-machine-learning domain experts
Timely and regular attendance
Equivalent combination of education and experience will be considered
Compliance with HIPAA and EnableComp data policies
Experience with healthcare data or another highly regulated industry highly preferred
Experience with structured or schema-constrained model output highly preferred
Broad reinforcement learning algorithms and advanced reward design experience highly preferred
Knowledge graphs or ontologies experience highly preferred
Synthetic data generation and validation experience highly preferred
Publications or open-source contributions in relevant fields highly preferred
Experience handling PHI under HIPAA highly preferred

Benefits

Comp & perks

Full-time employment
Professional growth and development opportunities
Tools, resources, and support for career growth
Equal opportunity, discrimination-free workplace
Reasonable accommodation for qualified individuals with disabilities
Remote work arrangement