About the Role
At Anyscale, we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray, a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. 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.
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
- 3+ years of experience in a customer-facing technical role in a dynamic, fast-paced, startup-like environment
- Strong organizational skills and ability to manage multiple customer needs simultaneously
- One of: Proficient as a machine learning engineer developing data pipelines for training, fine-tuning and inference/serving of LLMs OR 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 uplevel 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)