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Senior Customer Reliability Engineer

Job in Bellevue, King County, Washington, 98009, USA
Listing for: Weights & Biases
Full Time position
Listed on 2026-01-13
Job specializations:
  • IT/Tech
    Cloud Computing, Systems Engineer
Salary/Wage Range or Industry Benchmark: 165000 - 242000 USD Yearly USD 165000.00 242000.00 YEAR
Job Description & How to Apply Below
Position: Senior Customer Reliability Engineer - Weights & Biases

Senior Customer Reliability Engineer - Weights & Biases

Core Weave, the AI Hyperscaler™, has acquired Weights & Biases to create the most powerful end‑to‑end platform for developing, deploying, and iterating AI faster. The integration of our teams and technologies accelerates our mission to empower developers with the tools and infrastructure needed to push the boundaries of what AI can do.

About the Role

The Senior Customer Reliability Engineer plays a critical role in ensuring our highest‑value customers achieve exceptional stability, performance, and long‑term success. In this role, you will act as the technical owner and trusted engineering partner for a select group of strategic customers, helping them proactively optimize their use of our platform and quickly resolve complex issues.

What You’ll Do
  • Serve as the primary technical partner for a portfolio of top‑tier enterprise customers, owning reliability, performance, and operational success for their critical workloads.
  • Develop a deep understanding of each customer’s architecture and ML workloads to provide proactive guidance, best practices, and optimization strategies.
  • Troubleshoot and resolve complex problems across the Weights & Biases platform, APIs, integrations, and customer environments, driving both immediate fixes and long‑term solutions.
  • Reproduce, isolate, and document product issues, collaborating closely with engineering to ensure prioritization and sustainable resolution.
  • Build tools, scripts, and automation to diagnose issues quickly and enhance internal and customer‑facing troubleshooting workflows.
  • Provide architectural and operational recommendations to help customers scale experimentation, training pipelines, and generative AI workloads efficiently.
  • Mentor support engineers, ensuring consistent technical depth and high‑quality guidance across customer interactions.
  • Identify patterns across top‑tier accounts and advocate for systemic improvements that enhance platform reliability and customer experience.
  • Participate in incident response, post‑mortems, and internal documentation to continually elevate reliability standards.
  • Participate in a 24/7 on‑call rotation focused on supporting mission‑critical customer workloads.
Who You Are
  • 5+ years of experience in technical support, customer engineering, production engineering, reliability engineering, or a similar role supporting enterprise or strategic accounts.
  • Expert in Python, with strong debugging, profiling, and production‑grade development skills.
  • Strong background in computer science or software engineering (B.S. in CS or equivalent experience).
  • Experience running or supporting large‑scale, high‑availability systems (Kubernetes, GKE, cloud services, distributed systems).
  • Deep familiarity with the AI/ML ecosystem, including training frameworks (PyTorch, Tensor Flow) and generative AI stack (Hugging Face, Lang Chain, vector databases).
  • Skilled at diagnosing distributed systems, APIs, containerized environments, and multi‑tenant cloud architectures.
  • Exceptional communication skills, with the ability to interface effectively with customer engineering teams, executives, and internal stakeholders.
  • Demonstrated success partnering with product and engineering teams to drive reliability improvements and influence roadmap priorities.
  • Self‑driven, customer‑obsessed, and passionate about building reliable, scalable systems and great customer experiences.
  • Proficient with monitoring and observability tools (Datadog, Prometheus/Grafana, Open Telemetry, etc.) for debugging production environments.
Preferred
  • Experience with Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure).
  • Familiarity with GPU compute environments and distributed model training pipelines.
  • Previous experience in SRE, incident management, or cloud platform reliability roles.
  • Experience owning reliability for a specific major customer or “tenant” (e.g., dedicated instances, VPC deployments, on‑prem/isolated environments).
  • Experience participating in or running on‑call rotations and incident management processes.
Compensation

The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on…

Position Requirements
10+ Years work experience
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