Customer Support Engineer - Tier 3
Listed on 2026-03-01
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IT/Tech
AI Engineer, IT Support, Cloud Computing, Machine Learning/ ML Engineer
Customer Support Engineer – Tier 3
Core Weave, the AI Hyperscaler™, acquired Weights & Biases to create the most powerful end‑to‑end platform for developing, deploying, and iterating AI faster. Since 2017, Core Weave has operated a growing footprint of data centers in the US and Europe and was ranked as one of the TIME
100 most influential companies of 2024. By combining Core Weave’s industry‑leading cloud infrastructure with the best‑in‑class tools that AI practitioners know and love from Weights & Biases, we’re setting a new standard for how AI is built, trained, and scaled.
The integration of our teams and technologies is accelerating our shared mission: to empower developers with the tools and infrastructure they need to push the boundaries of what AI can do. From experiment tracking and model optimization to high‑performance training clusters, agent building, and inference at scale, we’re combining forces to serve the full AI lifecycle—all in one seamless platform.
Weights & Biases has long been trusted by over 1,500 organizations—including AstraZeneca, Canva, Cohere, OpenAI, Meta, Snowflake, Square, Toyota, and Wayve—to build better models, AI agents, and applications. Now, as part of Core Weave, that impact is amplified across a broader ecosystem of AI innovators, researchers, and enterprises.
As we unite under one vision, we’re looking for bold thinkers and agile builders who are excited to shape the future of AI alongside us. If you’re passionate about solving complex problems at the intersection of software, hardware, and AI, there’s never been a more exciting time to join our team.
As Weights & Biases and Core Weave unite to deliver the most powerful AI development platform, the Customer Support Engineer (Tier 3) plays a pivotal role in ensuring our most complex and business‑critical issues are resolved quickly and effectively.
What You’ll Do- Own and resolve Tier 3 technical escalations from the support team—highly complex or cross‑functional issues requiring deep technical investigation.
- Perform in‑depth troubleshooting and root‑cause analysis across Weights & Biases systems, APIs, and integrations.
- Reproduce, isolate, and document bugs for handoff to engineering.
- Develop diagnostic scripts, tools, and automation to improve internal troubleshooting efficiency.
- Serve as a technical advisor to Support Engineers (Tier 1 and Tier 2), mentoring on debugging methodologies and product architecture.
- Identify recurring patterns and propose systemic improvements to reduce future escalations.
- Participate in incident response, post‑mortems, and internal technical documentation.
- Contribute to knowledge‑base articles and internal wikis to ensure consistent handling of technical cases.
- Participate in a 24/7 on‑call rotation to provide support during weekends.
- 5+ years of professional experience in a technical support, software engineering, or escalations‑focused role.
- Expert in Python, with experience debugging, profiling, and developing production‑grade code.
- Strong background in computer science or software engineering (B.S. in CS or equivalent experience).
- Deep familiarity with modern AI and machine learning ecosystems—from model training and experimentation (PyTorch, Tensor Flow, etc.) to generative AI and LLM development (Hugging Face, Lang Chain, OpenAI, vector databases, etc.).
- Proficient in troubleshooting across distributed systems, APIs, containers, and have deep experience with multi‑tenant architectures and tenant isolation.
- Excellent communication skills with the ability to translate complex issues for both technical and non‑technical audiences.
- Demonstrated ability to collaborate effectively with product and engineering teams to drive issue resolution and product improvements.
- Self‑directed, curious, and passionate about improving both user experience and internal processes.
- Proficient with tools like Datadog, Grafana, etc., for production monitoring and incident debugging.
- Experience with Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure).
- Familiarity with GPU‑based compute environments and distributed training workloads.
- Previous experience in incident management, cloud…
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