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Software Engineer - Testing Frameworks

Baseten
San Francisco, USA
Full-time
Mid
Hybrid
Discovered 1 months ago
dockerkubernetespytest-toolpythonspark

Full Job Posting

RESPONSIBILITIES

  • Own Baseten's testing strategy end to end — define the standards, the tiers, and the tooling that engineering teams build against.
  • Build and maintain unit, integration, load and performance testing frameworks
  • Design end to end test infrastructure that provisions realistic dependencies on demand — ephemeral Kubernetes namespaces, containerized service dependencies, etc.
  • Build resilience and chaos testing capabilities: fault injection, network partition and latency simulation, pod and node failure scenarios, dependency degradation, and automated verification that our systems degrade gracefully and recover.
  • Attack test suite reliability head-on — flake detection and quarantine, test impact analysis and selective execution, parallelization, and aggressive reduction of end-to-end CI wall time.
  • Build observability into the testing layer itself: coverage reporting, test health dashboards, failure triage tooling, and clear signals about which areas of the codebase are under-tested.
  • Create project templates and shared libraries so new services start with a complete testing setup on day one.
  • Partner directly with product and infrastructure teams — embed where needed, understand their hardest testing problems, and turn one-off solutions into platform capabilities.
  • Mentor engineers across the org on testing practice and raise the collective bar through code review, documentation, and internal advocacy.

REQUIREMENTS

  • Strong proficiency in Go and/or Python, with hands-on experience building test tooling and libraries used by other engineers.
  • Deep experience with testing frameworks and their internals — pytest, Go's testing package, testify, testcontainers, or equivalents — including the ability to extend them, not just use them.
  • Experience designing integration test infrastructure for distributed systems, including ephemeral environment provisioning and dependency management.
  • Practical experience with load and performance testing tools (k6, Locust, Vegeta, JMeter, Gatling, or similar) and the judgment to interpret results and drive action from them.
  • Solid Kubernetes and Docker fundamentals — you can build test infrastructure that runs on and tests against real cluster environments.
  • Advanced understanding of CI/CD, including how to keep large test suites fast, deterministic, and trustworthy at scale.
  • A track record of measurably improving testing culture on an engineering team — you have opinions on what to test, what not to test, and where the ROI actually is.
  • Are excited about building foundational infrastructure and are comfortable working independently on ambiguous, high-impact technical challenges

BENEFITS

  • Competitive compensation, including meaningful equity
  • 100% coverage of medical, dental, and vision insurance for employee and dependents
  • Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
  • Paid parental leave
  • Fertility and family-building stipend through Carrot
  • Company-facilitated 401(k)
  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
  • Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
  • At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
  • We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

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