AI Engineer

Job not on LinkedIn

🔥 8 minutes ago

🎸 Tennessee – Remote

🎸 Tennessee – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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EnableComp

WebsiteLinkedInAll Job Openings

501 - 1000 employees

💼 Consulting

🛡️ Insurance

📦 Logistics

💰 Venture Round on 2022-07

Consulting • Insurance • Logistics

EnableComp is a company that specializes in revenue cycle management (RCM) for healthcare providers and health systems across the United States. They focus on processing complex claims related to Veterans Administration, Workers' Compensation, Motor Vehicle Accidents, and Out-of-State Medicaid, as well as denial management for all payer classes. By leveraging intelligent automation and their proprietary E360 RCM™ platform, EnableComp helps healthcare providers increase revenue, control costs, and streamline billing processes. With expertise in handling complex claims, the company ensures accurate and timely reimbursement, providing significant uplift to collections and improving the financial performance of its clients.

📋 Description

• 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

• 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

• 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