About the Role

You'll design, build, and scale the infrastructure that powers research workloads at Seldon Global. Working within the Engineering team, you'll own cloud compute, distributed systems, data storage, and experiment orchestration—improving reliability, performance, and resource efficiency as the platform grows. You'll partner closely with researchers and engineers to develop new capabilities and shape the underlying architecture.

What You'll Do

• Build and manage cloud compute infrastructure at scale to support research workloads.
• Design and optimize distributed workflow scheduling for performance and cost efficiency.
• Implement recovery procedures and safeguards to handle worker interruptions, application crashes, and partial results without duplicate work.
• Improve monitoring, logging, and diagnostic tools to help the team quickly identify and resolve system failures.

What We're Looking For

• Strong Python and Linux skills, including scripting, process management, and debugging.
• Experience operating services on a major cloud platform (AWS, GCP, Azure, etc.), including compute, storage, networking, and access management.
• Understanding of distributed systems concepts such as queues, timeouts, retries, and idempotency.
• Track record investigating production issues and making practical tradeoffs between reliability, complexity, and cost.
• Self-directed approach to work with strong follow-through; principled decision-making balanced with openness about uncertainty; collaborative problem-solving style.
• Experience with virtualization (KVM/QEMU), VM images and snapshots, or automating desktop applications is a plus.
• Familiarity with infrastructure-as-code tools (Terraform) and monitoring platforms (CloudWatch, Prometheus, Grafana) is a plus.
• Background in batch scheduling, experiment orchestration, or sandboxing untrusted code is a plus.

Compensation & Benefits

Competitive compensation plus equity. Comprehensive health, dental, and vision coverage. Visa sponsorship and relocation support. Professional development budget, premium AI tools, GPU access, and a Mac. Team off-sites and conference attendance. Transportation support, gym membership, and sports club subscriptions. Food stipend with nearly full meal coverage.

Location

Full-time or internship roles based in Zurich or San Francisco.