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
We are looking for an AI / ML Solutions Engineer to join Anyscale’s Professional Services team and work directly with customers to design, implement, and scale machine learning and AI workloads using Ray and Anyscale.
This role is ideal for a hands-on Machine Learning Engineer or MLOps Engineer who enjoys solving real-world production problems alongside customer teams. You will guide customers through architectural decisions, application refactors, and operational best practices as they adopt Ray for distributed training, data processing, inference, and ML workflows.
In addition to implementation work, you’ll play a key role in enabling customer ML and MLOps teams—helping them understand why architectural changes are needed and how to successfully operate Ray-based systems in production.
What You’ll DoCustomer Delivery & Implementation
Implement production AI / ML workloads using Ray and Anyscale, such as:
Distributed model training
Scalable inference and serving
Data preprocessing and feature pipelines
Work hands-on with customer codebases to refactor or adapt existing workloads to Ray
Architecture & Technical Guidance
Advise customers on ML system architecture, including:
Application design for distributed execution
Resource management and scaling strategies
Reliability, fault tolerance, and performance tuning
Guide customers through architectural and operational changes required to adopt Ray and Anyscale effectively
MLOps Enablement
Partner with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows
Support CI/CD, monitoring, retraining, and operational best practices
Help customers transition from experimentation to production-grade ML systems
Technical Enablement & Knowledge Transfer
Enable customer teams through working sessions, design reviews, training delivery, and hands-on guidance
Contribute feedback from the field to product, engineering, and education teams
Help develop reference architectures, examples, and best practices based on real customer use cases
Required Experience
5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or ML Systems Engineer
Strong proficiency in Python and experience building production ML systems
Hands-on experience with distributed systems or scalable ML frameworks (Ray, Spark, Dask, Kubernetes, etc.)
Experience with one or more of:
Distributed training (multi-node / multi-GPU)
Model serving and scalable inference
Data pipelines and workflow orchestration
Comfort working directly with customers in a consultative, problem-solving role
Strong communication skills and ability to explain technical tradeoffs clearly
Preferred Experience
Experience supporting or deploying ML platforms or internal ML infrastructure
Familiarity with cloud environments (AWS, GCP, Azure)
Exposure to MLOps tooling (MLflow, Airflow, Dagster, Kubeflow, etc.)
Prior experience in Professional Services, Consulting, or Customer Engineering roles
Work directly on real-world AI / ML systems at scale
Partner with leading ML teams across industries
Influence how Ray and Anyscale are adopted in production environments
Combine deep engineering work with customer impact
Competitive compensation, equity, and flexible remote work
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
Anyscale Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Anyscale and has not been reviewed or approved by Anyscale.
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Fair & Transparent Compensation — Pay is considered market-based with target ranges shown in postings and a stated market-based philosophy. Feedback suggests this clarity and consistency aid confidence in pay fairness.
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Equity Value & Accessibility — Equity is commonly included in offers and is positioned as a meaningful part of total compensation for many roles. Feedback suggests this equity participation enhances perceived overall pay competitiveness.
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Healthcare Strength — Health, dental, and vision coverage are described as robust with many plan options, alongside mental-health support and fertility benefits. Feedback suggests this strong core healthcare offering increases perceived benefits quality.
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What We Do
Distributed computing made simple Anyscale enables developers of all skill levels to easily build applications that run at any scale, from a laptop to a data center.








