Technical Support Engineer (W&B EMEA)

Coreweave; Greater London; On-site; GBP 45,000 - 65,000; Full time

Job summary

Weights And Biases by CoreWeave is seeking a proactive technical support specialist in London. You will quickly respond to user messages via email, chat, and forums, triaging issues and maintaining SLAs.

The role blends customer service with hands-on ML tooling support, offering opportunities to grow Python skills and work with modern ML frameworks. You will collaborate with engineering and product teams, build knowledge bases, and participate in a 24/7 on-call rotation.

Qualifications

• Python proficiency is required.
• 2+ programming experience in an engineering or CS setting.
• Experience with ML frameworks and libraries is a plus.
• Customer service experience in a technical SaaS environment.
• Familiarity with cloud services and containerization is preferred.

Responsibilities

• Respond to inbound user messages across email, live chat, and forums.
• Triage bugs and feature requests by severity and customer type.
• Track SLAs and ensure timely follow-ups for all messages.
• Collaborate with engineering and product teams to troubleshoot issues.

Skills

Python proficiency

Programming experience

Tools

Keras

Tensorborad

Tensorflow

Pytorch

Pytorch Lightning

Jupyter notebooks

colabs

matplotlib

Docker

AWS

GCP

Azure

Kubernetes

Job description

• Support is a deep part of our culture here at Weights And Biases by CoreWeave. We believe that the best way to build a great product is to listen to real users and follow their lead to shape our priorities and roadmap. In this role, you will work on a diverse set of problems in a fast-moving environment, collaborate cross-functionally with our team to support our users, and help shape our product
• Your main goal will be to quickly get answers to all user messages. Customers write in with highly technical questions, suggestions, or bug reports, and we need to give them timely responses to fulfill SLAs. Ideally, we’re looking for someone with technical skills who would like to support our customer base. If you’ve found yourself wanting to be more external but still build programming/machine learning skills, this is the role for you
• Quickly respond to all inbound support requests, including email, live chat, and community forums
• Triage bugs and requests based on customer type and severity of issue
• Track inbound and outbound responses to ensure contact SLAs are being met
• Maintain a fast response time for entire user base
• Collaborate with the engineering and product team when troubleshooting issues and providing feedback on features
• Recognize trends in user messages to help identify areas of improvement in internal or external documentation
• Learn Weights & Biases’ product features and build up knowledge base to resolve issues on your own
• Participate in a 24/7 on-call rotation to provide support during weekends
• This role requires that you will be working in our office in central London 3 - 5 days per week

A passion for connecting with real users and enabling them to be power users of the productPython proficiencyGood organization of assigned requests to oversee timely follow-up for every messageAnswer messages with a kind, thoughtful tone that makes users feel appreciated and connected to our teamProactively find ways to improve processes and collaborate internallyWork autonomously in a self-directed environmentInterest in machine learningExperience using any of the following: Keras, Tensorborad, Tensorflow, Pytorch, Pytorch Lightning, Jupyter notebooks, colabs, matplotlib and other ML frameworks and tools2+ Programming experience, from either an engineering role, a computer science degree, or personal projectsWondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren’t a 100% skill or experience matchPrevious experience in machine learningExperience in frontend frameworksCustomer service experience in a technical SaaS environmentExperience with Docker, AWS, GCP, AzureExperience with Kubernetes or other cloud infrastructures