Staff Software Engineer, Performance- Weights & Biases

About the role

The Performance Engineering team at Weights & Biases is seeking a Staff Engineer to take technical ownership of complex performance challenges across the W&B platform and infrastructure. The ideal candidate will design and lead experiments to improve system scalability and latency, develop standardized benchmarking and load testing frameworks, and drive initiatives to prevent regressions across product surfaces. They will collaborate closely with product, infrastructure, and SRE teams, combining deep technical expertise with a holistic understanding of system behavior.

Responsibilities

• Design and lead experiments to improve system scalability and latency
• Develop standardized benchmarking and load testing frameworks
• Drive initiatives to prevent regressions across product surfaces
• Collaborate closely with product, infrastructure, and SRE teams
• Blend investigation, architecture, and enablement to help teams measure, understand, and continuously improve performance

Requirements

• 8+ years of experience as a software engineer, with at least 2 years focused on performance optimization, systems scalability, or observability
• Proficiency in at least one of Go, Python, or TypeScript, with strong systems-level debugging and profiling skills
• Deep understanding of distributed systems concepts (caching, queuing, concurrency, resource contention, etc.) and their performance implications
• Experience designing and implementing load testing, benchmarking, or performance regression frameworks (e.g., Locust, Gatling, k6, custom solutions)
• Familiarity with metrics and tracing systems (Prometheus, Grafana, OpenTelemetry, Datadog, etc.) and performance data analysis
• Experience integrating performance measurement into CI/CD pipelines
• Ability to design experiments, analyze large datasets, and draw actionable conclusions
• Proven track record of driving cross-functional technical initiatives from design through adoption

Qualifications

• Preferred: Experience in performance engineering or SRE at scale (e.g., supporting multi-region, high-throughput systems)
• Familiarity with frontend performance monitoring and web vitals
• Experience building developer-facing tools or frameworks
• Background in data systems, observability, or ML infrastructure
• Experience contributing to open-source performance or benchmarking tools