Senior Engineer, Machine Learning

Virta Health

. Turn ambiguous clinical and operational questions into well-scoped ML tasks and build strong baselines .

Posted 11/4/2026full-timeRemote • United StatesSenior💰 $161,500 - $232,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying production-grade Machine Learning systems, with a strong foundation in predictive modeling, causal ML, and rigorous experimental design. Capable of collaborating across teams to enhance model quality while ensuring compliance with HIPAA regulations.

Highest-signal resume keywords

Machine Learning Systems DevelopmentPredictive ModelingCausal ML and ExperimentationStatistical ReasoningHIPAA Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Predictive ModelingTree-Based ModelsXGBoostTime-Series AnalysisCausal ModelsError AnalysisModel EvaluationAnomaly DetectionNLP/LLM-Based SystemsVariance-Reduction Techniques

Soft Skills

CommunicationCollaborationJudgment

Tools & Technologies

ML OpsProduct EngineeringProduct Analytics

Industry Keywords

Clinical MLHealth-TechPHIHIPAARegulated Data

About the role

Key responsibilities & impact

Turn ambiguous clinical and operational questions into well-scoped ML tasks and build strong baselines
Build predictive models that drive member care and partner with product engineering to deliver signals to members and care teams
Build retraining triggers, drift and anomaly detection, and continuous evaluation logic to keep models healthy in production
Design offline and online evaluations and perform error analysis on model failures
Build causal models validated against clinical experiments
Partner with Product Analytics on CUPED/CUPAC variance-reduction techniques
Build ML- and GenAI-derived signals for personalized coaching and member experiences
Lead complex ML initiatives from problem framing through production
Coordinate technical decisions and dependencies across Applied AI, ML Ops, Product Engineering, and Product Analytics
Share knowledge and practices that improve model quality and delivery

Requirements

What you’ll need

5+ years building, evaluating, and deploying production-grade Machine Learning systems for real-world use cases
Strong foundation in traditional ML, including predictive modeling, tree-based models such as XGBoost, and time-series analysis on structured longitudinal data
Rigorous evaluation and experimental design, including statistical reasoning, offline/online evaluation, and identifying leakage, selection bias, and confounding
Ability to explain model behavior, tradeoffs, uncertainty, and limitations to technical and non-technical stakeholders
Experience designing and analyzing experiments to determine causation rather than correlation
Depth in one or more of causal ML and experimentation, recommendation/ranking systems, predictive modeling, or NLP/LLM-based systems
Responsible use of AI-assisted development
Clinical or health-tech ML experience preferred
Experience with PHI, HIPAA-aware systems, or other regulated data preferred
Judgment about when traditional ML outperforms LLMs and when an LLM is appropriate
Ability to work in the United States
Compliance with Virta's security and privacy procedures for sensitive patient information governed by HIPAA

Benefits

Comp & perks

Equity
Remote-first work arrangement
Office hubs in Denver and San Francisco
Security and privacy training
Location-based compensation structure