Software Engineer – Fleet Health Instrumentation Intern

Actively pursuing a BS or MS in Computer Science, Computer Engineering, or a closely related quantitative field (e.g., Physics or Mathematics)
Solid understanding of distributed‑systems fundamentals, modern software‑engineering practices, and data‑modeling principles
Proficiency in at least one programming language—preferably Python or Go
Working knowledge of Linux, basic networking concepts, and Kubernetes container orchestration.

Design and build software that collects, transforms, and publishes health data about our global GPU fleet.
Develop micro-services and data pipelines in Go or Python that ingest and normalize data from many diverse sources—routing millions of records per day (Kafka, Airflow, Kinesis).
Instrument production infrastructure and workloads running on Kubernetes and bare-metal clusters; add tracing and metrics hooks for deeper insights.
Automate deployments and testing with CI/CD (GitLab, Argo) and IaC (Terraform), ensuring repeatable, low-touch releases.
Participate in the full lifecycle of cloud services—from design docs and code reviews through deployment, monitoring, and continuous improvement.
Collaborate with other engineers to debug live issues and turn post-incident insights into durable code fixes.
Contribute to internal tooling and dashboards that help engineers visualize fleet health, utilization, and capacity trends.

A systematic, analytical problem‑solving approach paired with clear written and verbal communication skills and a strong sense of ownership.
Demonstrated ability to debug, optimize, and automate code or workflows with minimal guidance.
Hands‑on experience building, deploying, and operating services in a public‑cloud or large on‑prem environment.