DatabricksSan Francisco, CAThis senior applied ML role builds and deploys optimization-driven machine learning systems for serverless infrastructure, spanning cluster management through query compilation. It requires production ML experience, cloud and distributed-systems knowledge, strong programming skills, and a master's degree in a related computational field.
Designs, develops, and maintains high-performance ML services and agentic AI systems, collaborating with ML engineers to scale from prototype to production. Requires 5+ years backend/ML experience, cloud-native tech, and strong architecture skills.
Leads automation and evaluation programs for AI Operations, architecting scalable workflows with LLMs, datasets, and quality systems. Requires 5+ years leading complex AI initiatives, cross-functional influence, and metrics-driven impact; familiarity with data pipelines preferred.
Builds high-performance infrastructure for brain reverse-engineering via large-scale AI models and neuroscience-informed simulations. Architects systems, optimizes RL environments, and scales research prototypes to production.
Build and evolve shared AI/ML infrastructure including LLM proxy server, observability tooling, and ML Ops platform capabilities. Focus on LLM Ops and ML Ops to improve how models are accessed, monitored, evaluated, deployed, and governed in production.
Sr. Software Engineer building and owning Bloomerang's agentic AI harness, including workflows, orchestration, guardrails, evals, and model integrations. Near-term focus on backend platform services (auth/identity in C#/.NET). Requires 8+ years experience, AI fluency, and ownership of reliable AI-driven development for nonprofit impact.