About the Role
Anyscale is on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. They commercialize Ray, a popular open-source project creating an ecosystem of libraries for scalable machine learning, used by companies like OpenAI, Uber, Spotify, Instacart, and Cruise. Anyscale aims to be the best place to run Ray, enabling developers and data scientists to scale ML applications from their laptop to a cluster without needing to be distributed systems experts. The company is backed by Andreessen Horowitz, NEA, and Addition with over $250 million raised. As a Customer Engineer (Customer Support Engineer), you 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. Given Anyscale is an evolving platform, this role requires close coordination with engineering teams to debug complex issues. This is an exciting opportunity for technically curious individuals passionate about ML/AI, LLM, vLLM, and the role of AI in next-generation applications, offering a chance to make a significant impact in a collaborative, fast-paced environment and build a new segment in this space.
Responsibilities
- 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
Requirements
- 7+ years of experience in a Machine Learning or Cloud Infrastructure 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
Qualifications
- 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)