Applied Research Lead, Reinforcement Learning
RunwayFull Time
Junior (1 to 2 years)
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 OpenAI, Uber, Spotify, Instacart, Cruise, 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.
RLlib is an open-source library for reinforcement learning that offers both high scalability and a unified API for a variety of applications. It is used by many high profile gaming and finance companies to build cutting-edge RL based systems. We're looking for software engineers with existing machine learning experience that are interested in continuing to enhance RLlib. We are looking for senior hires as well as less experienced but motivated individuals.
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Platform for scaling AI workloads
Anyscale provides a platform designed to scale and productionize artificial intelligence (AI) and machine learning (ML) workloads. Its main product, Ray, is an open-source framework that helps developers manage and scale AI applications across various fields, including Generative AI, Large Language Models (LLMs), and computer vision. Ray allows companies to enhance the performance, fault tolerance, and scalability of their AI systems, with some users reporting over 90% improvements in efficiency, latency, and cost-effectiveness. Anyscale primarily serves clients in the AI and ML sectors, including major companies like OpenAI and Ant Group, who rely on Ray for training large models. The company operates on a software-as-a-service (SaaS) model, charging clients a subscription fee for access to the Ray platform. Anyscale's goal is to empower organizations to effectively scale their AI workloads and optimize their operations.