Senior AI/ML Engineer
Own machine learning end to end, from modeling messy clinical data through production deployment, monitoring, and infrastructure. The role requires 7+ years of experience building scalable ML systems, strong software and data engineering skills, and proficiency with Python, SQL, and cloud platforms.
About the job
Responsibilities
- Build predictive models on clinical data at scale, including risk stratification, utilization prediction, and care-gap detection.
- Own the full machine-learning lifecycle: problem framing, feature engineering, training, evaluation, deployment, monitoring, retraining, and drift management.
- Convert unstructured clinical data such as PDFs, images, and doctors’ notes into structured records.
- Build ML infrastructure, including training and inference pipelines, experiment tracking, model versioning, and evaluation systems.
- Collaborate with founders, engineers, and customers to identify and prioritize high-leverage ML problems.
- Develop models for hospitalization prediction, clinical-document classification, and extraction from freeform medical notes and scanned documents.
- Build or operate cloud backend systems, model-serving infrastructure, data pipelines, and production monitoring.
Requirements
- 7+ years building machine-learning systems that operate on real-world data at scale.
- Strong knowledge of regression, tree-based methods, feature engineering, dimensionality reduction, and deep learning.
- Experience building and training models directly, rather than only orchestrating APIs.
- Demonstrated delivery of ML systems with measurable production results.
- Strong software-engineering fundamentals and experience with large-scale cloud backend systems.
- Ability to own training pipelines, model serving, and monitoring end to end.
- Strong SQL and data-engineering skills, including working with large datasets and building model-input pipelines.
- Located in San Francisco or the Bay Area, or willing to relocate.
Nice-to-haves
- Healthcare standards and technologies, including FHIR, HIE, IHE, EHR/EMR, NPI, TEFCA, ADT, HL7, HEDIS, RAF, SNOMED, LOINC, and ICD-10.
- Founder experience or experience as the first or only ML hire at an early-stage startup.
Compensation and Benefits
- Competitive compensation and equity package.
- Family Platinum health, dental, and vision insurance.
- 401(k) with matching.
- Flexible work from home or in-office.
- Complimentary meals when working in the office.
- Quarterly company off-sites.
- Company-provided MacBook.
- Unlimited paid time off.
Skills
Machine Learning, Python, Deep Learning, Regression, Gradient Boosting, Feature Engineering, Dimensionality Reduction, SQL, AWS, TypeScript, Infrastructure As Code, Model Serving, FHIR, Snowflake
Similar jobs
ML Engineering jobs
Traba
New York, NYBuild and deploy production AI-agent systems, including their harnesses, evaluations, orchestration, and supporting services. The role requires 5+ years of software engineering experience, production LLM or agent experience, and strong Python or TypeScript/Node.js skills.
SentiLink
United States
Leads and manages an applied machine learning team developing production fraud detection and identity verification models. The role combines people leadership with hands-on technical work and requires substantial ML experience, production deployment expertise, and experience in risk-focused domains.
Airbnb
United States
Builds and productionizes machine learning systems for trust and safety, including abuse detection, autonomous AI agents, and evaluation frameworks. The role requires 5+ years of applied ML experience, strong Python skills, experience with LLMs and scalable pipelines, and a relevant advanced degree or equivalent background.
6sense
San Francisco, CA
Owns end-to-end production machine learning systems, including NLP, LLM, agentic, ranking, and recommendation capabilities. Requires 8+ years of industry experience, strong Python and cloud ML expertise, and the ability to deliver explainable AI products with cross-functional and customer impact.
Instacart
United StatesDevelop and deploy production machine learning models for real-time inventory and shelf-stocking intelligence at scale. The role requires 5+ years of production ML experience, strong Python and ML framework skills, cloud and data pipeline expertise, and a bachelor's degree or equivalent experience.