Job description

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 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. About the role Anyscale is looking for a Software Engineer to join the Platform and Infrastructure team. Anyscale aims to provide the next generation of tools and infrastructure to make developing and running distributed AI applications in the cloud as easy as on your laptop. As part of the team, we build the scalable, secure, and robust backbone that enables this vision, ensuring that our "infinite laptop" vision scales to meet the most demanding distributed AI workloads in the world. Our team is responsible for both the control plane, which orchestrates cluster management, scheduling, and user access, and the data plane, which ensures high-performance execution of distributed workloads. We are seeking a talented Software Engineer with a strong background in control plane and data plane development, along with expertise in Kubernetes, container orchestration, and cloud-native infrastructure. You will play a crucial role in designing, implementing, and optimizing the critical infrastructure that powers Anyscale's cloud platform. You will have the opportunity to work on open-source Ray, contribute to our infinite laptop proprietary product, and develop seamless integration between the two, while also delivering high-impact features for our customers. A snapshot of projects you may work on - Design, build, and scale services that orchestrate Ray clusters across cloud and on-prem environments, supporting both VM-based and Kubernetes-based deployments - Optimize control plane components for large-scale, distributed AI/ML workloads - Build intelligent scheduling and resource management systems for heterogeneous compute clusters - Develop features to enhance the reliability, performance, scalability, and observability of Anyscale-managed Ray workloads - Support and optimize accelerator integration (e.g., GPUs, TPUs). - Handle container image management and dependency resolution for distributed workloads - Participate in code reviews, design and architecture discussions - Provide on-call support, working closely with customer and field teams to troubleshoot infrastructure issues - Collaborate with leading distributed systems and machine learning experts to push the boundaries of AI infrastructure We'd love to hear from you if have - Bachelor's degree in Computer Science, Engineering, or equivalent practical experience - 3+ years of experience writing high-quality production code - Hands-on experience in building and maintaining highly available, scalable, and performant distributed system - Expertise in cloud-native technologies (AWS, Azure, GCP) and Kubernetes-based deployments - Deep understanding of networking, security, and authentication mechanisms in cloud environment - Familiarity with observability stacks (Prometheus, Grafana etc) - Proficiency in Go and Python - Knowledge of low-level operating system foundations (Linux kernel, file systems, containers) WHY ANYSCALE - We're on a mission to make scalable computing effortless. Ray is the AI Compute Engine at the center of some of the world's most powerful AI platforms - Our tech is in production at companies like OpenAI, Uber, Spotify, Instacart, and Cruise - We're backed by Andreessen Horowitz, NEA, and Addition, with $250M+ raised to date - Recent partnerships with Azure, CoreWeave, and Google Cloud are putting AI-native compute directly into enterprise environments - Competitive salary and equity, plus health/dental/vision coverage (many plans up to 99% employer-covered) - We offer flexible time off, paid parental leave, and mental health support 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 drive.google.com and the Right to Work posters in English and Spanish drive.google.com

Requirements

Must-haves

Our team is responsible for both the control plane, which orchestrates cluster management, scheduling, and user access, and the data plane, which ensures high-performance execution of distributed workloads.
A snapshot of projects you may work on
Design, build, and scale services that orchestrate Ray clusters across cloud and on-prem environments, supporting both VM-based and Kubernetes-based deployments
Optimize control plane components for large-scale, distributed AI/ML workloads
Build intelligent scheduling and resource management systems for heterogeneous compute clusters
Develop features to enhance the reliability, performance, scalability, and observability of Anyscale-managed Ray workloads
Support and optimize accelerator integration (e.g., GPUs, TPUs).
Handle container image management and dependency resolution for distributed workloads
Participate in code reviews, design and architecture discussions
Provide on-call support, working closely with customer and field teams to troubleshoot infrastructure issues
Collaborate with leading distributed systems and machine learning experts to push the boundaries of AI infrastructure
We'd love to hear from you if have
Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
3+ years of experience writing high-quality production code
Hands-on experience in building and maintaining highly available, scalable, and performant distributed system
Expertise in cloud-native technologies (AWS, Azure, GCP) and Kubernetes-based deployments
Deep understanding of networking, security, and authentication mechanisms in cloud environment
Familiarity with observability stacks (Prometheus, Grafana etc)
Proficiency in Go and Python
Knowledge of low-level operating system foundations (Linux kernel, file systems, containers)
We're on a mission to make scalable computing effortless. Ray is the AI Compute Engine at the center of some of the world's most powerful AI platforms
Our tech is in production at companies like OpenAI, Uber, Spotify, Instacart, and Cruise
We're backed by Andreessen Horowitz, NEA, and Addition, with $250M+ raised to date
Recent partnerships with Azure, CoreWeave, and Google Cloud are putting AI-native compute directly into enterprise environments

Nice-to-haves

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Keywords to mirror

machine learningaimlkubernetesawsazuregcpgopython

Platform: ashby
Effort: quick

Benefits

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Dental

Vision

Pto

Parental Leave