Applied AI Scientist, Healthcare ML for Home Care

Sprinter Health; San Francisco (CA); Hybrid; USD 180,000 - 250,000; Full time

Benefits offered by this job

Meaningful pre‑IPO equity

Medical, dental, and vision plans 100%

Flexible PTO

401(k) with match

Parental leave policy

HSA + FSA contributions

Life insurance and disability coverage

Free daily lunch in‑office

Annual learning stipend

Relocation assistance

Job summary

Sprinter Health is seeking an Applied Scientist, AI to translate complex healthcare problems into ML solutions that improve access to care. You will operate across research, product, engineering, and clinical operations to build and evaluate models with rigorous error analysis and real‑world impact.

You will partner with ML engineers to productionize models, validate assumptions with clinicians, and clearly communicate limitations and tradeoffs to leadership. Hybrid Bay Area role.

Qualifications

• MS or PhD in computer science, statistics, machine learning, applied math, operations research, biomedical informatics, epidemiology, or related field

Responsibilities

• Turn ambiguous healthcare, product, and operational problems into well‑posed ML, AI, ranking, optimization, NLP, or LLM‑based tasks
• Build strong baselines and improve on them efficiently using appropriate modeling approaches
• Develop models across traditional ML, deep learning, NLP, and LLM‑based approaches
• Design offline and online evaluations that are honest, measurable, and predictive of real‑world impact
• Choose metrics suited to imbalanced, delayed, noisy, and partially observed healthcare outcomes
• Run careful error analysis and use it to improve model quality and product fit
• Identify leakage, bias, confounding, and other data artifacts before production
• Explore messy real‑world data and assess label quality for modeling readiness
• Partner with ML engineering to productionize models reliably and define production readiness
• Work with clinicians and subject‑matter experts to validate assumptions and understand edge cases
• Explain model tradeoffs, uncertainty, and limitations to product and leadership
• Write experiment docs and summarize findings for deployment decisions
• Pressure‑test results for real, robust, and useful production use

Skills

Python

PyTorch

scikit-learn

NumPy

pandas

Polars

Hugging Face

Matplotlib

NLP

LLMs

Education

MS/PhD in CS or related fields

Tools

PyTorch

scikit-learn

NumPy

pandas

Polars

Hugging Face

Matplotlib

Job description

Sprinter Health is seeking an Applied Scientist, AI to translate complex healthcare problems into ML solutions that improve access to care. You will operate across research, product, engineering, and clinical operations to build and evaluate models with rigorous error analysis and real‑world impact.

You will partner with ML engineers to productionize models, validate assumptions with clinicians, and clearly communicate limitations and tradeoffs to leadership. Hybrid Bay Area role.