Develops and optimizes large-scale simulation and ML training pipelines using Ray.io and Kubernetes to validate autonomous vehicle behaviors. Requires 6+ years experience optimizing distributed systems, Python proficiency, and AWS knowledge.
192k – 241k/yr
Hybrid6+ YOEData Engineering
About the role
Responsibilities
Improve the cost efficiency, reliability, and performance of validation and simulation pipelines
Create production-grade APIs, SDKs, and tools to enable validations of autonomous behaviors
Improve ML training pipelines supporting the autonomous behavior org
Qualifications
Bachelor’s degree in Computer Science or related field and 6+ years of industry experience
Experience optimizing large-scale distributed systems for cost and efficiency
Experience with AWS or similar providers
Proficiency with Python and familiarity with C++
Bonus Qualifications
Exposure to machine learning workloads (training, inference, data generation) from a cost optimization perspective
Background in algorithmic optimization or performance investigation
Experience with Ray.io, particularly Ray Core and Ray Data
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