Sprinter Health

1 day ago

Applied Scientist, AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Build and iterate machine learning and AI models to improve access to care and operational outcomes in high-stakes healthcare use cases. Turn ambiguous product and operational questions into well-scoped prediction, ranking, optimization, NLP, and LLM tasks. Develop baselines, design offline/online evaluations, run rigorous error analysis, and address leakage, bias, and confounding. Partner with ML engineering and clinical stakeholders to productionize models and clearly communicate tradeoffs, uncertainty, and limitations.

Location: San Francisco, Menlo Park

Workplace: Hybrid

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Turn ambiguous healthcare, product, and operational problems into well-posed ML/AI tasks (prediction, ranking, optimization, NLP, LLM).
•Build strong baselines and improve them efficiently using appropriate traditional ML, deep learning, NLP, and LLM approaches.
•Design honest offline and online evaluations and select metrics for imbalanced, delayed, noisy, and partially observed outcomes.
•Run careful error analysis and identify label leakage, selection bias, confounding, and other data artifacts before production.
•Partner with ML engineering and clinical stakeholders to productionize models and explain tradeoffs, uncertainty, limitations, and expected impact clearly.

Pay and Benefits

Salary: USD 180,000 - 260,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVision401kEquityLearning BudgetRelocationParental Leave

Key Requirements

•MS or PhD (or equivalent applied experience) in computer science, statistics, machine learning, applied math, operations research, biomedical informatics, epidemiology, or a related quantitative field.
•Built, evaluated, and iterated on machine learning or AI models for real-world use cases.
•Design rigorous offline evaluations, experiments, or analyses that inform production or product decisions.
•Depth in LLMs, ranking, NLP, uncertainty quantification, causal inference, optimization, or healthcare AI.
•Experience working with healthcare data (e.g., claims, EHR, clinical notes) and PHI/HIPAA-aware systems or other sensitive regulated data.

Experience:HealthcareMachine learningLLMsNLPRegulated data

Education:Master's

Skills:Scientific rigorEvaluation focusError analysisStakeholder communicationAmbiguity handling

Tech Stack:PythonPyTorchScikit-learnNumPyPandasPolarsHugging FaceMatplotlibNLPLLMClaude CodeCursor

Company Brief

Sprinter Health

Operates mobile and home-based primary care services focused on delivering in-home medical visits, chronic care management, and coordinated care for patients who face barriers accessing clinic-based care.

Industry: Healthcare Providers

Website

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Sprinter Health

1 day ago

Applied Scientist, AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Location: San Francisco, Menlo Park

Workplace: Hybrid

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Turn ambiguous healthcare, product, and operational problems into well-posed ML/AI tasks (prediction, ranking, optimization, NLP, LLM).
•Build strong baselines and improve them efficiently using appropriate traditional ML, deep learning, NLP, and LLM approaches.
•Design honest offline and online evaluations and select metrics for imbalanced, delayed, noisy, and partially observed outcomes.
•Run careful error analysis and identify label leakage, selection bias, confounding, and other data artifacts before production.
•Partner with ML engineering and clinical stakeholders to productionize models and explain tradeoffs, uncertainty, limitations, and expected impact clearly.

Pay and Benefits

Salary: USD 180,000 - 260,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVision401kEquityLearning BudgetRelocationParental Leave

Key Requirements

•MS or PhD (or equivalent applied experience) in computer science, statistics, machine learning, applied math, operations research, biomedical informatics, epidemiology, or a related quantitative field.
•Built, evaluated, and iterated on machine learning or AI models for real-world use cases.
•Design rigorous offline evaluations, experiments, or analyses that inform production or product decisions.
•Depth in LLMs, ranking, NLP, uncertainty quantification, causal inference, optimization, or healthcare AI.
•Experience working with healthcare data (e.g., claims, EHR, clinical notes) and PHI/HIPAA-aware systems or other sensitive regulated data.

Experience:HealthcareMachine learningLLMsNLPRegulated data

Education:Master's

Skills:Scientific rigorEvaluation focusError analysisStakeholder communicationAmbiguity handling

Tech Stack:PythonPyTorchScikit-learnNumPyPandasPolarsHugging FaceMatplotlibNLPLLMClaude CodeCursor

Company Brief

Sprinter Health

Industry: Healthcare Providers

Website