P-78
At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.
As part of the ML/AI Environments team you will build the system that enables the AI researchers and engineers to set up their desired training and serving environments. You’ll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses helping thousands of our customers democratize AI within their organizations. We’re building the infrastructure that powers the next generation of AI.
The impact you will have
- Build the infrastructure that enables ML and AI users to configure training and serving environments easily, reliably and reproducibly.
- Collaborate with other AI infrastructure teams to build the features that customers need to get more from the Databricks platform. Examples include improving performance of setting up virtual environments for short training and data processing sessions, improving observability to help customers debug when runs fail, etc.
- Interact with turnkey customers and product managers to envision new features and identify areas for improvement.
- Shape how developers and data scientists build and interact with AI on Databricks.
What we look for
- 5+ years of experience in backend or infrastructure engineering with a focus on building systems
- Strong programming skills in Python, Scala or Java
- Experience with distributed systems, scalable APIs, or cloud-native infrastructure
- Familiarity with service-oriented architecture, deployment pipelines, and system observability
- Strong product and ownership mindset — you care about building the right solution, not just any solution
- Strong understanding of dependency management technologies including virtual environments or containerization technologies.
