AI/ML Solutions Engineer
Listed on 2026-01-12
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Cloud Computing, Data Engineer
Location: California
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.
AboutThe 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.
- 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
- 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
- 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
- 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
- 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 trade‑offs clearly
- 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.
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