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SeniorOfficeSan Francisco

Machine Learning Engineer

A
Anyscale
Уровень
Senior
Формат
Office
О роли

Описание вакансии

About the role

The Customer Engineer will play a crucial role in the customers’ post-sale journey - helping them to onboard, adopt and grow on Anyscale, troubleshooting and resolving open customer tickets and driving consumption.

Anyscale is an ever evolving platform and hence will require close co-ordination with our engineering teams to debug complex issues. This is an exciting role for those who are technically curious and passionate about ML/AI, LLM, vLLM and the role of AI in next generation applications. It’s an opportunity to make a significant impact in a collaborative, fast-paced environment while building a new segment in this space.

In this role, you’ll be able to
  • Resolve customer issues and help in their successful adoption of Anyscale platform
  • Be a technical advisor, and internal champion for our key customers
  • Own customer issues end-to-end, from troubleshooting, triaging, escalations and eventual resolution
  • Participate in our follow-the-sun customer support model to ensure continuity in resolving high priority tickets
  • Keep track of open customer bugs and feature requests to influence prioritization and provide timely customer updates upon resolution
  • Contribute towards improvement of internal tools and documentation of playbooks, guides and best practices etc. based on observed patterns
  • Habitually provide feedback and collaborate cross-functionally with product and engineering teams to address customer issues with a focus on improving the product experience
  • Build and maintain strong relationships with technical stakeholders within customer accounts
Qualifications
  • 7+ years of experience in a Machine Learning role in a dynamic, fast-paced, startup-like environment
  • Strong organizational skills and ability to manage multiple customer needs simultaneously
  • Proficient at developing data pipelines for training, fine-tuning and inference/serving of LLMs
  • Experience running and optimizing infrastructure for distributed ML workloads on the major cloud platforms (AWS/EKS, GCP/GKE or Azure/AKS)
  • Excellent communication and interpersonal skills.
  • Strong sense of ownership, self-motivation and eagerness to acquire new skills and do new things
  • Willingness to up-level the knowledge and skills of your peers through mentorship, trainings and shadowing
Bonus
  • Experience with Ray
  • Knowledge of MLOps platforms
  • Knowledge of container orchestration platforms (e.g., Kubernetes), infrastructure as code (e.g. Terraform), CI/CD tools (e.g. Github Actions)
Стек и навыки

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