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Anyscale

Scales AI workloads with Ray platform

Engineering Manager - Ray Data

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAIn-person

About the Job

Requirements

  • At least 7 years of software engineering experience, including at least 2 years directly managing engineers, ideally at a high-growth startup.
  • A record of building high-performing distributed teams and helping them scale quickly while maintaining a good culture.
  • Experience building and managing teams across geographic locations, preferably in the United States and India.
  • Ability to maintain a high hiring bar, motivate the team, coach and mentor engineers, and handle performance management issues.
  • Deep technical knowledge of distributed systems and data-intensive systems, such as data processing engines, query engines, or database internals.
  • Enough hands-on depth in Python and performance-sensitive systems code to review designs and work through performance and stability problems alongside the team.
  • A strong track record of execution, urgency, and prioritization.
  • Effective written and verbal communication with engineers, customers, and an open source community.

Responsibilities

  • Set the technical direction and roadmap for open source Ray Data, balancing community needs, customer needs, and Anyscale's product goals.
  • Drive execution of the team's key projects, from design review through release.
  • Hire, coach, and grow a team of distributed systems and data infrastructure engineers.
  • Run the team day to day, including planning, prioritization, project tracking, on-call, and release quality.
  • Stay technically hands-on through design and code review, performance investigations, and escalations on critical production issues.
  • Represent Ray Data in the open source community by working with external contributors and maintainers, reviewing Ray Enhancement Proposals, keeping GitHub issue and pull request triage healthy, and growing the contributor base.
  • Partner with the Ray Core, Ray Train, Ray Serve, and Anyscale platform teams on cross-library features and end-to-end performance.
  • Work with product management, field engineering, and customers, including AI-native companies running Ray Data at large scale, to understand their workloads and turn them into roadmap priorities.
  • Build and maintain a team culture of collaboration, ownership, and high engineering standards.
  • Communicate the team's work to a broader audience through talks, tutorials, blog posts, and at Ray Summit.

Desired Qualifications

  • Experience leading or maintaining a widely used open source project, including working with external contributors and project governance.
  • Hands-on experience with Ray, Spark, Flink, Beam, or similar engines.
  • Experience with Apache Arrow, columnar formats, or table formats such as Iceberg and Delta Lake.
  • Experience with GPU workloads, LLM or multimodal batch inference, or data loading for large-scale model training.
  • Experience operating data or ML infrastructure in production.

About the Company

Anyscale

Scales AI workloads with Ray platform

Anyscale helps enterprises run AI workloads at scale by providing a software platform built around the Ray open-source framework. The core product enables users to deploy, manage, and optimize distributed AI tasks—from training to inference—across large clusters, with features that handle scaling, fault tolerance, and resource management. The platform is delivered as a software-as-a-service, so customers pay a subscription to access tools for running Generative AI, large language models, computer vision, and other ML workloads efficiently and reliably. Unlike others who focus on individual components, Anyscale combines Ray’s distributed execution with enterprise-ready management, monitoring, and optimization to productionize AI applications. The company’s goal is to help organizations deploy AI workloads faster, at scale, with predictable performance and cost efficiency.

Company size
501-1,000
Company stage
Acquired
Total funding
$259.6M
Headquarters
San Francisco, CA
Founded
2019

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