- 4+ years of software experience, shipping and operating production data or AI systems as a hands-on IC
- Building and evaluating ML models in production (tabular, embeddings, LLM-based)
- Data engineering at scale: Python and SQL
- Apache Spark
- AWS data stack (EMR, Athena, Glue, Iceberg)
חולץ מתיאור המשרה · מתעדכן אוטומטית
תיאור המשרה המלא
המשרה המקורית · נשמר לעיוןAbout Vi & the role • Vi is an enterprise AI platform for health enterprises - healthcare, biopharma, and wellness. We deploy agentic AI and predictive models into production environments where the output drives the next best actions for patients, care teams, and operations to deliver ROI and improve health outcomes. • The Vi Platform is the shared layer under every Vi application. It turns data, models, agents and compliance into services that every product uses to onboard clients, reach patients and measure results, so a capability is built once and reused everywhere. We are looking for an AI Engineer to take those services from idea to production, and to keep them running as they grow. • You will be part of the Vi Platform team, reporting to the VP of R&D. This is a hands-on IC role at the crossroads of data science, software engineering and cloud infrastructure: you design the service, you build every layer of it, you ship it, you measure what it does for the products that use it, and you maintain and extend it with the features its users need.
Requirements: • 4+ years of software experience, with a track record of shipping and operating production data or AI systems as a hands-on IC. • Data science and ML in production: Building and evaluating models (tabular, embeddings, LLM-based), deciding what "good" means for a service, and measuring it. • Data engineering at scale: Python, SQL and Spark on AWS (EMR, Athena, Glue, Iceberg), workflow orchestration (Airflow), and performance work on large joins and feeds. • Backend and full-stack engineering: Production APIs and services in Python and TypeScript, and enough React to ship an internal console yourself. • Cloud and DevOps: AWS, Infrastructure as Code (CDK), Docker, CI/CD and monitoring; you own the infrastructure of your service, not just the code. • LLM and agent engineering: Shipping LLM features with evaluation behind them, and an AI-first development workflow with coding agents as a daily tool. • High ownership and velocity: You scope, design, build, ship and support without a hand-off. You write the design doc and the user guide, and your work stands up for review.
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- 4+ years of software experience, shipping and operating production data or AI systems as a hands-on IC, Building and evaluating ML models in production (tabular, embeddings, LLM-based), Data engineering at scale: Python and SQL, Apache Spark, AWS data stack (EMR, Athena, Glue, Iceberg)