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Convert ambiguous healthcare and operational problems into well-scoped ML/AI, ranking, optimization, NLP, or LLM tasks; build and evaluate models, run error analysis, design honest evaluations, partner with engineering and clinical stakeholders, and productionize reliable models with clear communication of tradeoffs and limitations.

Own and build canonical data models and metric definitions using dbt and cloud warehouses. Create tests, documentation, lineage, and data quality checks; reconcile metrics across teams and payer customers; partner with analysts, data scientists, product, engineering, and finance; optimize warehouse performance, cost, and PHI-aware access patterns.

Founding ML engineering hire to design and build production ML systems: training and inference pipelines, serving, feature workflows, monitoring, retraining, governance, and operational practices. Partner across engineering, data, product, and applied science to productionize models, implement observability, prevent degradation, and set platform standards and hiring bar for future ML engineers.

Lead and conduct ML research aligned to Sprinter Health's strategy: define research agenda, design rigorous experiments, develop novel methods and evaluations, publish and patent findings, translate research into production-ready tools, and collaborate with clinicians and cross-functional teams to validate and deploy clinically robust AI solutions.

Design and deploy optimization, forecasting, and simulation models to match clinicians to patients under constraints. Build baselines, run evaluations and experiments, and productionize decision systems in partnership with engineering, product, and operations to improve operational metrics like cost per visit and clinician utilization.

Design and build backend services, APIs, and full-stack features that power patient booking, clinician routing, logistics, and device integrations. Own projects 0→1, solve scheduling/dispatch challenges, integrate external health systems, and collaborate with product, data, ops, and clinical teams to ship reliable, secure healthcare software.

Build and scale backend and full-stack systems powering patient booking, clinician routing, logistics, and device integrations. Design APIs, data models, and services, solve scheduling/dispatch challenges, integrate external health systems, and own projects from 0->1 while collaborating with product, data, ops, and clinical teams.

Lead and develop a team of engineers, focusing on recruitment, mentorship, and performance management, while driving technical excellence in a fast-paced environment.

Design and implement logistics optimization algorithms, develop predictive models, and build simulations for patient scheduling and routing in healthcare.

The Senior Software Engineer will explore AI solutions in healthcare, having experience in full-stack/backend development and startup culture.