Sprinter Health
Applied Scientist, AI
$180K–$260K
San Francisco, CA · Hybrid · Full-time · Posted Jul 20, 2026
- Education
- MS or PhD in a quantitative field, or exceptional applied experience that substitutes for formal graduate training (listed as an edge).
About the job
Build and evaluate machine learning and AI systems for healthcare, product, and operational problems, partnering with engineering and clinical teams to support real-world deployment and impact.
What you'll do
- Translate ambiguous problems into measurable ML/AI tasks; build and improve models.
- Design rigorous evaluations, analyze errors and data issues, and assess real-world impact.
- Partner with engineering and clinical stakeholders to prepare models for production and communicate findings, limitations, and tradeoffs.
What they ask for
- Experience building, evaluating, and iterating on ML or AI models for real-world use cases.
- Experience turning ambiguous problems into measurable modeling tasks and designing rigorous evaluations or experiments.
- Experience with messy real-world data and statistical reasoning, experimental design, or error analysis.
- Python and standard ML/AI tooling, such as PyTorch, scikit-learn, NumPy, pandas, Polars, Hugging Face, or Matplotlib.
Nice to have
- MS or PhD in a quantitative field, or exceptional applied experience substituting for graduate training.
- Depth in LLMs, ranking, NLP, uncertainty quantification, causal inference, optimization, or healthcare AI; production impact or healthcare data experience is also an edge.
Pay
$180K – $260K (base salary)
Tools
Python, PyTorch, scikit-learn, NumPy, pandas, Polars, Hugging Face, Matplotlib
AI focus
Develop, evaluate, and help productionize traditional ML, deep learning, NLP, and LLM-based approaches for healthcare and operational use cases; assess model reliability, bias, leakage, uncertainty, and real-world impact.
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