4 months ago
Remote, United StatesStaff+
Base Salary
$250k - $280k/yr
Responsibilities
- Define system architecture for end-to-end AI and LLM-powered products using claims, medical records, and clinical documentation.
- Build evaluation frameworks using LLM-as-a-Judge, offline metrics, and online experiments aligned with accuracy, auditability, and clinical and regulatory risk.
- Create data flywheels from clinician and auditor reviews and use labeled data for model fine-tuning and improved detection precision.
- Explore patient-level digital twins from clinical charts for unified processing and data presentation across payment, risk, and quality products.
- Lead ranking and prioritization systems that surface high-value claims, audits, and care gaps for human review.
- Establish reusable platform patterns including shared context stores, evaluation harnesses, and feature pipelines.
- Partner with engineering, product, clinical, and analytics teams on success criteria, roadmaps, and production rollouts.
- Mentor senior engineers, raise ML engineering standards, set company-wide standards, and influence enterprise AI/ML strategy.
- Complete assigned performance-review responsibilities, special projects, and other duties as assigned.
Requirements
- PhD in a quantitative discipline such as computer science or engineering, statistics, or operations research covering advanced statistics, machine learning, and AI.
- 12+ years of industry experience building production ML systems at scale.
- Deep expertise in at least two of LLM evaluation, retrieval-augmented generation, ranking, or large-scale classification.
- Proven experience leading end-to-end ML projects from problem framing through production impact.
- Strong experimentation discipline including A/B testing, causal inference, metric design, and opportunity mining.
- Proficiency in Python, PyTorch, SQL at scale, Presto, Trino, Spark, and Airflow.
- Ability to drive cross-functional alignment across engineering, product, and analytics.
- Experience with LLM-as-a-Judge evaluation pipelines and supervised fine-tuning of embedding or reranking models is highly valued.
- Healthcare data experience involving claims, electronic health records, or clinical coding such as ICD, CPT, or HCC is highly valued.
- Experience designing ML systems for regulated, auditable, or high-stakes domains and familiarity with sensitive-data frameworks such as HIPAA are highly valued.
- Experience building organization-wide canonical data services or platform-level ML infrastructure is highly valued.
- Ability to communicate, solve problems critically, work independently, interpret data, and make timely workflow decisions.
- Must be able to perform duties with or without reasonable accommodation.
Benefits
- Base compensation ranges from $250,000 to $280,000 per year, with eligibility for discretionary bonus consideration.
- Medical, dental, vision, disability, and life insurance coverage.
- 401(k) savings plan and paid family leave.
- 9 paid holidays per year and 17–27 days of paid time off depending on level and length of service.
- Remote work arrangement with all interviews conducted virtually.
- Applicants must provide a dedicated secure work area, high-speed internet connectivity, and office setup and maintenance.
- Applications are assessed on a rolling basis; the anticipated application window closes October 6, 2026, subject to change.
Tech Stack
Categories
About Cotiviti
Cotiviti builds analytics software and tech-enabled services that help U.S. health insurers and government payers improve payment integrity, risk adjustment, and quality measurement, and also provides supplier audit and procure-to-pay accuracy for retailers. It operates a SaaS and services model focused on reducing improper payments and enhancing clinical and coding compliance. Headquartered in South Jordan, Utah, Cotiviti is privately held, and its customers serve the majority of U.S. healthcare consumers—over 300 million members and patients.