Anyscale

AI/ML Solutions Engineer

Anyscale

full-time

Posted on:

Location Type: Remote

Location: United States

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Tech Stack

Distributed SystemsKubernetesNode.jsPythonRaySpark

About the role

  • Implement production AI / ML workloads using Ray and Anyscale, such as:
  • - Distributed model training
  • - Scalable inference and serving
  • - Data preprocessing and feature pipelines
  • 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

Requirements

  • 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.
Benefits
  • Competitive compensation
  • Equity
  • Flexible remote work

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
Pythondistributed model trainingscalable inferencedata preprocessingfeature pipelinesresource managementfault toleranceperformance tuningCI/CDworkflow orchestration
Soft skills
consultative problem-solvingstrong communicationcustomer advisingtraining deliveryhands-on guidance