Note: The job is a remote job and is open to candidates in USA. Cotiviti is seeking a Senior Principal Machine Learning Engineer to lead the design and delivery of end-to-end ML/AI systems. The role involves defining technical strategy and driving cross-functional alignment to improve payment accuracy and quality outcomes for payers.
Responsibilities
- Define system architecture for AI/LLM-powered products end to end over claims, medical records, and clinical documentation
- Build and own evaluation frameworks (LLM-as-a-Judge, offline metrics, online experiments) aligned to accuracy, auditability, and clinical and regulatory risk — because outputs inform payment and compliance decisions
- Drive the data flywheel: convert expert clinician and auditor review decisions into high-quality labeled data, and close the loop with fine-tuning of models to lift detection precision
- Explore building patient-level digital twins from clinical charts for unified processing layer and data presentation across payment, risk and quality
- Lead ranking and prioritization systems that surface the highest-value claims, audits, and care gaps for human review, improving both reviewer efficiency and financial impact
- Establish reusable platform patterns — shared context stores, evaluation harnesses, feature pipelines — that compound value across product surfaces and lines of business
- Partner across engineering, product, clinical, and analytics teams to align on success criteria, roadmap priorities, and production rollout
- Mentor senior engineers and elevate organization-wide standards in ML craftsmanship, experimentation rigor, and system design
- Sets company-wide standards
- Acts as a thought leader beyond Cotiviti to elevate the reputation and visibility of Cotiviti in the industry
- Influences the enterprise AI/ML strategy at an executive level
- Complete all responsibilities as outlined in the annual performance review and/or goal setting
- Complete all special projects and other duties as assigned
Skills
- PhD in a quantitative discipline such as Computer Science/Engineering, Statistics, Operations Research covering Advanced Statistics, Machine learning and AI
- 12+ years of industry experience building production ML systems at scale
- Deep expertise in two or more of: LLM evaluation, retrieval-augmented generation (RAG), ranking, or large-scale classification
- Proven track record leading end-to-end ML projects, from problem framing through production impact
- Strong experimentation discipline: A/B testing, causal inference, metric design, and opportunity mining
- Proficiency in Python (PyTorch), SQL at scale (Presto / Trino / Spark), and distributed pipeline tooling (Airflow)
- Demonstrated ability to drive cross-functional alignment across engineering, product, and analytics
- Experience building LLM-as-a-Judge evaluation pipelines aligned to quality, risk, and accuracy criteria
- Hands-on supervised fine-tuning of embedding or reranking models with measurable production gains
- Experience with healthcare data (claims, electronic health records, or clinical coding such as ICD, CPT, or HCC)
- Background designing ML systems in regulated, auditable, or high-stakes domains (healthcare, finance, or fraud, waste, and abuse detection)
- Familiarity with building systems that handle sensitive data under frameworks such as HIPAA
- Background building canonical data services or platform-level ML infrastructure adopted organization-wide
- Applied mathematics, statistics, or quantitative PhD background
- LLM ecosystem: RAG pipelines, LLM-as-a-Judge evaluation, prompt engineering, supervised fine-tuning
Benefits
- Discretionary bonus consideration
- Medical, dental, vision, disability, and life insurance coverage
- 401(k) savings plans
- Paid family leave
- 9 paid holidays per year
- 17-27 days of Paid Time Off (PTO) per year, depending on specific level and length of service with Cotiviti
Company Overview
Company H1B Sponsorship