Senior AI Engineer

Location: Remote within the United States; Franklin, Tennessee is listed as a location.

Company

hirify.global is hiring for its Information Technology department.

What you will do

• Capture specialized knowledge from domain experts and represent it in structured, usable form.
• Analyze source materials and datasets, resolve quality and coverage issues, and create training and evaluation datasets with automated and human validation.
• Design reinforcement learning environments, reward functions, verifiers, and language-model training workflows using supervised and reinforcement learning methods including PPO, DPO, and GRPO.
• Run reproducible experiments with versioned configurations, experiment tracking, ablations, baselines, and compute budgeting.
• Design evaluation frameworks, metrics, benchmarks, structured experiments, and A/B tests for language models and agents.
• Document failures and results and present findings to engineers, domain experts, and business leaders.

Requirements

• Bachelor’s degree in computer science, machine learning, statistics, or a related field; equivalent hands-on experience is considered. An MS or PhD is preferred.
• 3+ years of hands-on experience training or fine-tuning language models.
• Demonstrated reinforcement learning experience, including designing an environment and reward function end to end and training a policy in it.
• Working knowledge of PPO, DPO, or GRPO for language models, including their failure modes.
• Strong Python and PyTorch skills, with fluency in the Hugging Face ecosystem and parameter-efficient fine-tuning techniques.
• Experience building and evaluating LLM-based agents or multi-turn systems, and designing language-model evaluations with held-out sets and automated grading.
• Ability to analyze complex documentation, translate it into precise structured and testable forms, write clearly about experiments, and collaborate with non-ML domain experts.
• Timely and regular attendance, ability to perform each essential duty satisfactorily, and compliance with reasonable accommodation requirements.
• Equivalent combinations of education and experience are considered.

Nice to have

• Healthcare data or experience in another highly regulated industry.
• Experience training models to produce structured or schema-constrained output.
• Broad reinforcement learning experience and advanced reward design.
• Knowledge representation experience with knowledge graphs or ontologies.
• Experience generating and validating synthetic training data.
• Publications or open-source contributions in reinforcement learning, language-model fine-tuning, or model evaluation.
• Experience handling sensitive data, including protected health information (PHI) under HIPAA.

Culture & Benefits

• 100% hands-on individual contributor role owning experiments from design through code, training, and results.
• Approximately half of the role focuses on reinforcement learning and model training; the remainder covers knowledge engineering, data analysis, and evaluation.
• Close, sustained collaboration with domain experts is required.
• Data, training, and evaluation approaches must adapt as the underlying knowledge changes.
• All work must comply with HIPAA and hirify.global data policies, using de-identified or synthetic data wherever possible.
• The role is full-time and remote within the United States.