{"id":2443498,"url":"https://alion.io/job/enablecomp-ai-engineer-remote","title":"AI Engineer (REMOTE)","company":{"id":4046,"name":"EnableComp","domain":"enablecomp.com","url":"https://alion.io/company/enablecomp","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":114000,"max_usd":240000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":73},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"DPO","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GRPO","optional":false},{"name":"HIPAA","optional":false},{"name":"Hugging Face","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"PPO","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Synthetic Data","optional":false}],"status":"live","first_seen_at":"2026-10-13T12:09:49Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-14T00:38:59Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"EnableComp provides Specialty Revenue Cycle Management solutions for healthcare organizations, leveraging over 24 years of industry-leading expertise and its unified E360 RCM™ intelligent automation platform to improve financial sustainability for hospitals, health systems, and ambulatory surgery centers (ASCs) nationwide. Powered by proprietary algorithms, iterative intelligence from 10M+ processed claims, and expert human-in-the-loop integration, EnableComp provides solutions across the revenue lifecycle for Veterans Administration, Workers’ Compensation, Motor Vehicle Accidents, and Out-of-State Medicaid claims as well as denials for all payer classes. By partnering with clients to supercharge the reimbursement process, EnableComp removes the burden of payment from patients and provider organizations while enabling accelerated cash, higher and more accurate yield, clean AR management, reduced denials, and data-rich performance management. EnableComp is a multi-year recipient the Top Workplaces award and was recognized as Black Book's #1 Specialty Revenue Cycle Management Solution provider in 2024 and is among the top one percent of companies to make the Inc. 5000 list of the fastest-growing private companies in the United States for the last eleven years.\nPosition Summary\nThe AI Engineer is a hands-on individual contributor who builds, trains, and evaluates machine learning models. The role combines knowledge engineering and data analysis with applied reinforcement learning, and owns work end to end, from data and experiment design through training, evaluation, and reporting.\nThe ideal candidate brings practical reinforcement learning experience, strong engineering discipline, and the ability to collaborate closely with domain experts and communicate results to technical and non-technical audiences.\nKey Responsibilities\nWork with domain experts to capture specialized knowledge and represent it in structured, usable form.\nAnalyze source material and datasets for quality, consistency, and coverage, and resolve issues with the appropriate stakeholders.\nPerform exploratory and statistical analysis to inform data, modeling, and evaluation decisions.\nCreate and curate training and evaluation datasets, using both automated and human validation.\nDesign reinforcement learning environments, reward functions, and verifiers.\nTrain and fine-tune language models using supervised and reinforcement learning methods such as PPO, DPO, and GRPO.\nEstablish baselines, run ablations, and diagnose training issues such as reward hacking, instability, and data leakage.\nFollow the research literature and bring promising techniques into practice.\nManage experiments rigorously, including versioned configurations, reproducible runs, experiment tracking, and compute budgeting.\nDesign and extend evaluation frameworks, metrics, and benchmarks.\nCompare models and approaches through structured experiments and A/B testing.\nDocument results, failures, and next steps in clear technical write-ups.\nPresent findings to engineers, domain experts, and business leaders in language each audience can act on.\nRequirements & Qualifications\nBachelor’s degree in computer science, machine learning, statistics, or a related field; MS or PhD preferred. Equivalent hands-on experience will be considered.\n3+ years of hands-on experience training or fine-tuning language models.\nDemonstrated reinforcement learning experience, including designing an environment and reward function end to end and training a policy in it.\nWorking knowledge of policy optimization methods for language models, such as PPO, DPO, or GRPO, including their failure modes.\nStrong Python and PyTorch skills, with fluency in the Hugging Face ecosystem and parameter-efficient fine-tuning techniques.\nExperience building and evaluating LLM-based agents or multi-turn systems.\nExperience designing evaluations for language models, including held-out sets and automated grading.\nAbility to analyze complex, detailed documentation and translate it into precise, structured, testable form.\nClear technical writing, with the ability to explain an experiment and its results concisely.\nComfort working directly with domain experts who are not machine learning practitioners.\nExperience working with healthcare data or in another highly regulated industry is highly preferred.\nExperience training models to produce structured or schema-constrained output is highly preferred.\nExperience with a broad range of reinforcement learning algorithms and advanced reward design is highly preferred.\nExperience with knowledge representation approaches such as knowledge graphs or ontologies is highly preferred.\nExperience generating and validating synthetic data for model training is highly preferred.\nPublications or open-source contributions in reinforcement learning, language model fine-tuning, or model evaluation is highly preferred.\nExperience handling sensitive data, including protected health information (PHI) under HIPAA is highly preferred.\nTimely and regular attendance.\nEquivalent combination of education and experience will be considered\nTo perform this job successfully, an individual must be able to perform each essential duty satisfactorily. Reasonable accommodation may be made to enable qualified individuals with disabilities to perform the essential functions.\nSpecial Considerations and Prerequisites\nPractices and adheres to EnableComp’s Core Values, Vision and Mission.\nThis is a 100% hands-on individual contributor role. The AI Engineer owns experiments from design through code, training, and results.\nExpect roughly half of the role to focus on reinforcement learning and model training, with the remainder split between knowledge engineering, data analysis, and evaluation.\nSuccess requires sustained, close collaboration with domain experts and a genuine working understanding of the subject matter.\nThe underlying knowledge evolves over time. The AI Engineer must design data, training, and evaluation approaches that adapt to change without starting over.\nAll work must comply with HIPAA and EnableComp data policies, using de-identified or synthetic data wherever possible.","description_format":"text","description_chars":6179,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Business Process Outsourcing (BPO)","Revenue Cycle & Medical Billing"],"lifecycle":[{"event":"open","at":"2026-10-13T12:49:03Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":20,"reasons":["conf:1","win:early"],"computed_at":"2026-10-14T02:22:39Z"},"pay":null,"html_url":"https://alion.io/job/enablecomp-ai-engineer-remote","json_url":"https://alion.io/job/enablecomp-ai-engineer-remote.json","meta":{"generated_at":"2026-10-14T02:22:39Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":3587,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-15T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":4046},"rest":"https://alion.io/mcp/rest/get_company?id=4046"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fenablecomp-ai-engineer-remote"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fenablecomp-ai-engineer-remote"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fenablecomp-ai-engineer-remote"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/enablecomp-ai-engineer-remote\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fenablecomp-ai-engineer-remote"}]}