Engineering Manager, Ray Data

Anyscale is looking for an engineering leader to manage the open source Ray Data team. Ray Data is the Python-native data processing engine for AI workloads on Ray. It handles multimodal and structured data and powers batch inference, data loading for distributed training, and large-scale preprocessing. The team owns the open source library end to end, including:

• The streaming execution engine, including scheduling, backpressure, and resource management across CPUs and GPUs

• Batch inference for LLMs and multimodal models, including integrations with inference engines such as vLLM

• Data loading for production training workloads with Ray Train and popular ML frameworks

• Connectors for data sources and formats such as Parquet, Iceberg, Delta Lake, Lance, and cloud object storage

• Performance, stability, and fault tolerance at large scale

This is a first-line engineering management role where you'll lead a team of engineers, stay involved in technical design and code, and own the team's roadmap within the open source project. Ray Data has a large and active community, so you'll also work closely with external contributors to review designs, guide technical direction, and support the project's continued growth and success. The team plays an important role in the broader Ray ecosystem and contributes directly to Anyscale's success.

• 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 world-class team of distributed systems and data infrastructure engineers

• Run the team day to day: 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: work with external contributors and maintainers, review Ray Enhancement Proposals, keep GitHub issue and PR triage healthy, and grow 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

• Help us build and shape a world-class company

• 7+ years of software engineering experience, including 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 with building and managing teams across geographic locations, preferably in US and India

• Ability to keep 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 great track record of execution, with a sense of urgency and excellent prioritization skills

• Effective written and verbal communication with engineers, customers, and an open source community

• 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

We believe in transparent pay practices. The anticipated base salary range for this role is $267,000 - $375,000. Final salary depends on experience, relevant skills, qualifications, and market considerations. In addition to base pay, eligible employees receive equity awards and enjoy a comprehensive benefits package designed to support their health, well-being, and financial future.