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Senior Machine Learning Engineer, DevOps/SRE
Summary by AIEngineer.careers
Senior Machine Learning Engineer, DevOps/SRE is a MLOps Engineer role (full-time). with Roku. in SAN JOSE, US. Compensation shown: $149K–$361K. Imported listing (source: jobs-radar.com). Apply on the employer's site (jobs-radar.com).
Imported listing (source: jobs-radar.com) · Apply on jobs-radar.com
SAN JOSE · US
$149K–$361K
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from jobs-radar.com
Roku is seeking a Senior Machine Learning Engineer, DevOps/SRE to join their Advertising Performance team. The role involves designing and operating scalable cloud infrastructure for ML workloads, building CI/CD systems for ML models, and ensuring observability and reliability. The ideal candidate has extensive experience in DevOps, SRE, and ML infrastructure, with expertise in Kubernetes, cloud platforms, and ML tools.
Responsibilities
- Lead design and operation of scalable cloud infrastructure for ML workloads across AWS and GCP.
- Architect and improve CI/CD systems for ML models and platform services.
- Own and evolve low-latency infrastructure for real-time model inference.
- Define and enforce observability standards for ML systems.
- Participate in on-call rotation and incident response.
- Partner with data scientists and ML engineers to improve platform usability.
- Champion operational excellence through automation, resilience, disaster recovery.
Requirements
- BS or MS in Computer Science, Engineering, or related quantitative field.
- 8+ years of experience in DevOps, SRE, or ML infrastructure, including 4+ years supporting large-scale ML/AI systems.
- Strong programming skills in Python, Scala, or Java.
Roku
San Jose · US · 3600+ employees
Roku, Inc. is a leading American technology company that pioneered streaming to the TV, providing a purpose-built operating system (Roku OS) for streaming players and smart TVs. The company operates a platform that connects users to streaming content, enables content publishers to monetize audiences, and provides sophisticated advertising tools.
