Software Engineer (Machine Learning)

Key Skills

Apache Flink, Apache Hadoop, AWS, Google Cloud Platform (GCP), Kubernetes-K8s, Machine learning techniques, PyTorch, Spark Core, TensorFlow

Job Description

About the role:

Anyscale is looking to hire strong individuals to develop open source machine learning libraries.

The software industry largely operates on a messy zoo of specialized distributed systems such as Spark, Horovod, and TensorFlow Serving. These systems cannot easily be composed together and used as elements of a larger application. On the Machine Learning Ecosystem team at Anyscale, we are developing a rich ecosystem that will allow developers to import powerful distributed libraries and compose them together to build new applications.

Part of this work will be open source as part of Ray, which is a distributed Python execution engine as well as an ecosystem of libraries for scalable machine learning.

About the Libraries team:

The Libraries team’s mission is to make it really easy to do distributed machine learning on Ray and Anyscale. Specifically, our team maintains and develops features for a broad number of libraries — including Ray Train (distributed deep learning), Ray Tune (distributed hyperparameter tuning), RLlib (reinforcement learning), and XGBoost-on-Ray.

Our team is the most user-facing engineering team on the open source side, collaborating with ML engineering teams at organizations like Shopify, Uber, and Bytedance.

As part of this role, you will:

• Build elastic, scalable, fault-tolerant distributed machine learning libraries that power the next generation of machine learning platforms around the world
• Benchmark and improve performance and scalability of different machine learning libraries
• Work closely with other engineers developing Ray to build core abstractions and simplify machine learning services for open source users
• Work closely with the open source community (with ML researchers, ML engineers, data scientists) to scope and build new abstractions for scalable machine learning

We'd love to hear from you if you have:

• Solid background in algorithms, data structures, system design
• Experience with machine learning frameworks and libraries (PyTorch, Tensorflow)

Bonus points!

• Experience working with a cloud technology stack (AWS, GCP, Kubernetes)
• Experience building machine learning training pipelines or inference services in a production setting
• Experience with big data tools (Spark, Flink, Hadoop)
• Experience in building scalable and fault-tolerant distributed systems

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
• Paid Time Off
• Commute reimbursement
• 100% of in office meals covered