POSTED Oct 15

Machine Learning Engineer - Distributed Training

at AnyscaleSan Francisco, CA

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About Anyscale:

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 OpenAIUberSpotifyInstacartCruise, 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.

About The Role
We’re looking for passionate, motivated engineers excited to build infrastructure and tools for the next generation of machine learning applications. We’re hiring exceptional Software Engineers for our distributed training team, which develops and maintains widely adopted open-source machine learning libraries.

We’re particularly interested in engineers who can help shape and execute a vision for the future of ML training infrastructure. We welcome both Individual Contributors and technically inclined individuals with experience managing small teams.

About The Distributed Training Team
The Distributed Training team drives the development and optimization of Ray’s distributed training libraries, focusing on features and performance enhancements for large-scale machine learning workloads. They are responsible for building and maintaining core libraries like Ray Train (for distributed model training) and Ray Tune (for distributed hyperparameter tuning). You’ll collaborate closely with the Ray Core and Ray Data teams to create impactful, end-to-end solutions, and have the exciting opportunity to work directly with Machine Learning teams around the globe, shaping products that are transforming the AI landscape.
About The Role
We’re looking for passionate, motivated engineers excited to build infrastructure and tools for the next generation of machine learning applications. We’re hiring exceptional Software Engineers for our distributed training team, which develops and maintains widely adopted open-source machine learning libraries.

We’re particularly interested in engineers who can help shape and execute a vision for the future of ML training infrastructure. We welcome both Individual Contributors and technically inclined individuals with experience managing small teams.

About The Distributed Training Team
The Distributed Training team drives the development and optimization of Ray’s distributed training libraries, focusing on features and performance enhancements for large-scale machine learning workloads. They are responsible for building and maintaining core libraries like Ray Train (for distributed model training) and Ray Tune (for distributed hyperparameter tuning). You’ll collaborate closely with the Ray Core and Ray Data teams to create impactful, end-to-end solutions, and have the exciting opportunity to work directly with Machine Learning teams around the globe, shaping products that are transforming the AI landscape.

As part of this role, you will:

  • Develop scalable, fault-tolerant distributed machine learning libraries that power leading ML platforms
  • Create an exceptional end-to-end experience for training machine learning models
  • Solve complex architectural challenges and transform them into practical solutions
  • Contribute to and engage with the open-source community, collaborating with ML researchers, engineers, and data scientists to build new scalable machine learning abstractions
  • Share your work and expertise with a broader audience through talks, tutorials, and blog posts
  • Collaborate with a team of experts in distributed systems and machine learning
  • Work directly with end-users to iterate on and enhance the product based on their feedback
  • Partner with engineering and product managers to nurture a talented team of software engineers
  • Play a key role in building and shaping a world-class company
  • We'd love to hear from you if have:

  • Minimum 5+ years of experience building, scaling, and maintaining software systems in production environments
  • Strong fundamentals in algorithms, data structures, and system design
  • Proficiency with machine learning frameworks and libraries (e.g., PyTorch, TensorFlow, XGBoost)
  • Experience designing fault-tolerant distributed systems
  • Solid architectural skills
  • Bonus points if:

  • Experience with cloud technologies (AWS, GCP, Kubernetes)
  • Hands-on experience building ML training platforms in production
  • Background in managing and maintaining open-source libraries
  • Experience leading small teams to achieve ambitious technical goals
  • Familiarity with Ray
  • Compensation:

  • At Anyscale, we take a market-based approach to compensation. We are data-driven, transparent, and consistent. The target salary for this role is $170,112 ~ $237,000. As the market data changes over time, the target salary for this role may be adjusted.
  • This role is also eligible to participate in Anyscale's Equity and Benefits offerings, including the following:
  • Stock Options
  • Healthcare plans, with premiums covered by Anyscale at 99%
  • 401k Retirement Plan
  • Wellness stipend
  • Education stipend
  • Paid Parental Leave
  • Flexible Time Off
  • Commute reimbursement
  • 100% of in office meals covered
  • Anyscale Inc. is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law. 

    Anyscale Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish
    About Anyscale:

    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 OpenAIUberSpotifyInstacartCruise, 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.

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