ML Customer Engineer: Onboard, Support & Scale AI Apps

Anyscale; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Anyscale is seeking a Customer Engineer to guide customers through onboarding, adoption, and growth on the Anyscale platform. You will troubleshoot complex issues, coordinate with engineering, and help customers maximize their use of Ray-based ML workloads.

The role emphasizes strong communication, ownership, and collaboration across product and engineering teams in a fast-paced environment.

Qualifications

• 7+ years of experience in a Machine Learning role in a startup-like environment.
• Excellent communication and interpersonal skills.
• Strong ownership mindset and willingness to mentor peers.
• Experience developing data pipelines for training, fine-tuning, and inference/serving of LLMs.
• Ability to manage multiple customer needs simultaneously.
• Experience running distributed ML workloads on major cloud platforms.
• Willingness to collaborate with product and engineering teams to improve the product experience.

Responsibilities

• Resolve customer issues and ensure successful adoption of Anyscale platform.
• Act as a technical advisor and internal champion for key customers.
• Own customer issues end-to-end from troubleshooting to resolution.
• Participate in follow-the-sun support to resolve high-priority tickets.
• Track customer bugs and feature requests to influence prioritization and updates.
• Contribute to internal tools and documentation with best practices.

Skills

ML experience

Strong communication

Ownership

Data pipelines

Multi-tasking

Mentorship

Customer focus

Tools

AWS/EKS

GCP/GKE

Azure/AKS

Kubernetes

Terraform

Github Actions

Job description

Anyscale is seeking a Customer Engineer to guide customers through onboarding, adoption, and growth on the Anyscale platform. You will troubleshoot complex issues, coordinate with engineering, and help customers maximize their use of Ray-based ML workloads.

The role emphasizes strong communication, ownership, and collaboration across product and engineering teams in a fast-paced environment.