Software Engineer, Anyscale
ML Developer Experience
$226-283k
+ Equity
3+ days a week in office
Scalable compute for AI and Python
Be an early applicant
Scalable compute for AI and Python
501-1000 employees
Be an early applicant
$226-283k
+ Equity
3+ days a week in office
501-1000 employees
Company mission
To make scalable computing effortless.
Role
Who you are
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
- 5+ years of experience writing high-quality production code
- A solid background in algorithms, data structures, and system design
- Experience working with modern machine learning tooling — PyTorch, MLflow, data catalogs, and similar
- Hands-on experience building and operating highly available services in production
- Strong product instincts and a track record of shipping developer-facing tools that people choose to use
Desirable
- Experience building and maintaining open-source projects
- Experience building and operating machine learning infrastructure in production
- Experience building highly available serving systems
- Experience using Ray
What the job involves
- Anyscale is looking for a Software Engineer to join the ML Developer Experience (MLDevX) team
- MLDevX owns the experience layer of the Anyscale platform: the interfaces through which users and coding agents discover, configure, run, observe, debug, and productionize AI workloads
- Every user journey crosses this layer through the CLI, SDKs, APIs, UI, Workspaces, MCP, or the workflows and integrations built on top of them
- Together, these form the user’s primary interface into Anyscale, turning distributed computing from a systems problem back into a coding problem
- We build the common contracts, tools, control-plane services, and architecture that power these surfaces
- You will work across the stack from developer tooling to cloud infrastructure and the Ray runtime
- Manage long-running operations and make failures across jobs, tasks, actors, nodes, and GPUs easier to diagnose
- The systems you build must scale with the platform, remain predictable through failures, and be intuitive for developers, programmable for applications, and operable by coding agents
- This is a high impact individual-contributor role with end-to-end ownership
- You will work directly with users and field teams to identify high leverage problems, shape the product and technical design, and build and operate the solution
- The scope spans the AI workload loop - data preparation, fine-tuning and post-training, serving, evaluation, and iteration as well as the developer loop: code, submit, monitor, debug, optimize, and re-submit
- We are looking for someone with strong product judgment, a willingness to understand the user base, and the technical depth to build high quality software for everyone from a developer learning Ray for the first time to an AI-native company or enterprise running production workloads at scale
- Build the next generation of developer tooling and MLOps capabilities on Ray, designed for both developers and coding agents
- Develop an agent-first CLI and cohesive SDK, API, and MCP surfaces with self-discovery, structured errors, dry-run support, and consistent behavior across platform resources
- Work across the Anyscale Workspaces stack to improve the path from local code to distributed execution, including environments, dependencies, images, authentication, workload submission, and debugging
- Build cohesive experience, tools and frameworks for the AI development lifecycle, including data preparation, fine-tuning and post-training, evaluation, production serving, dataset management, experiment tracking, and lineage
- Build the path from a trained model to a reliable production endpoint, including model registration, deployment workflows, performance benchmarking, and LLM-specific service metrics
- Surface observability across the CLI, SDK, UI, and agent-facing interfaces so users can diagnose failures across jobs, tasks, actors, nodes, and GPUs
- Design open integrations using durable standards such as OpenAI-compatible APIs and OpenTelemetry, along with stable Jobs and Services interfaces for external orchestrators
- Design and operate the highly available backend services and platform architecture that power these capabilities across serverless and bring-your-own-cloud environments
- Work closely with users and field teams to scope, ship, and iterate on the product, and collaborate with distributed systems and machine learning experts to push the boundaries of AI infrastructure
Our take
Anyscale operates at the heart of the rapidly expanding AI infrastructure market, where organizations increasingly need systems built to handle large-scale, multimodal, and compiled AI workloads. Founded by the original creators of Ray - an open-source distributed computing framework powering companies like Netflix, Uber, and OpenAI - Anyscale was built to overcome the "AI complexity wall" that legacy compute can't handle. And its providing an AI-native platform that can scale seamlessly from as ingle machine to thousands of GPUs.
The company's impact comes from making distributed AI development faster, easier, and far more efficient. By pairing Ray's flexible compute framework with managed clusters, advanced developer tooling, and performance optimization, Anyscale removes the operational burden of scaling AI. Companies like Canva, Recursion, and RunwayML have seen dramatic gains in utilization, speed and cost. So it's fair to say Anyscale has helped teams deliver AI applications faster and with greater reliability.
The company recently strengthened its position through major partnerships with Azure, CoreWeave, and Google Cloud, bringing AI-native compute directly into enterprise environments. New capabilities like RayTurbo, Kubernetes-native deployment, and first-party managed Ray services make it easier than ever to run high-performance AI at scale. With model sizes and multimodal workloads growing rapidly, Anyscale is in a good position to remain a foundational platform for organizations building the next generation of AI systems.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
133% employee growth in 12 months
Company
Funding (last 2 of 4 rounds)
Aug 2022
$99m
SERIES C
Dec 2021
$100m
SERIES C
Total funding: $259.6m
Company benefits
- Health, Vision, and Dental Care: We offer a wide range of health, dental, and vision coverage options for you and your family—including many plans that are 99% covered by Anyscale
- Fertility Benefits & Paid Parental Leave: Anyscalers can access fertility benefits through Kindbody. Team members can take advantage of 12 weeks of paid leave following the arrival of a new little one.
- Flexible Time Off: We believe all team members should be able to rest up and recharge when needed, which is why we’ve embraced a flexible time off policy at Anyscale.
- Learning & Wellness Stipend: We believe in investing in our #1 asset: our people. We offer a monthly learning and wellness stipend so employees can better themselves at work or pursue personal interests.
- In-Office Meals: Lunch is served everyday in our San Francisco and Palo Alto Offices. Dinner, too, if you’re ever working late. And did we mention boba runs?
- Commute Reimbursement: Whether you’re hopping on public transit or driving yourself to work, Anyscale covers a portion of your commuting costs each month.
- Paid Volunteer Time Off: Give back to the causes and communities you love with paid time off specifically for volunteer work.
- Mental Health Benefits: All Anyscalers can take advantage of included mental health benefits through our Headspace offering.
Company HQ
Yerba Buena, San Francisco, CA
Leadership
Phillip Moritz
(Co-Founder & CTO)Phillip graduated from the University of California, Berkeley with a PhD in Computer Science.
Keerti Melkote
(CEO)Prior to joining Anyscale in 2024, Keerti spent 5 years at Hewlett Packard Enterprise at the President of Intelligent Edge. They also co-founded Aruba Networks where they spent nearly 20 years in roles including CTO and CEO.
Jooree Na
(CFO)Prior to joining Anyscale in 2024, Jooree spent over 5 years at Confluent, joining as a Director of Technical Accounting & Reporting before working through different roles and becoming the VP of Finance.
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