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Senior Machine Learning Engineer, DevOps/SRERoku • San Jose, Arizona, United States
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Senior Machine Learning Engineer, DevOps/SRE

Roku
  • US
    San Jose, Arizona, United States
  • US
    San Jose, Arizona, United States
Jetzt Bewerben

Über

About the team The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers, and Roku. The systems and solutions span multiple disciplines and technologies to perform real‑time multi‑objective optimization across distributed systems at large scale and with low latency. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning, Experimentation, and Inference Platform that powers the entire landscape, which we continuously evolve over time.
About the role We are seeking a talented and experienced Senior Software Engineer, MLOps/DevOps, to join the Advertising Performance team and play a critical role in supporting and scaling our Machine Learning infrastructure. The ideal candidate has a strong background in DevOps/SRE practices, cloud infrastructure management, and MLOps tooling — with a passion for building platforms that accelerate ML experimentation and deployment at internet scale.
You will partner closely with ML Scientists and Engineers to streamline the end‑to‑end ML lifecycle across training, evaluation, deployment, and monitoring — on top of a modern, cloud‑native stack running on GCP and AWS using Kubernetes, Apache Airflow, Spark, Ray, MLflow, Chronon, etc.
For California Only - The estimated annual salary for this position is between $148,750 - $361,000 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.
What you’ll be doing
Lead the design and operation of scalable, production‑grade cloud infrastructure for ML workloads across AWS and GCP, including GPU/TPU‑based training and inference environments
Architect and improve CI/CD systems for ML models and platform services to enable fast, reliable, and safe production releases
Own and evolve low‑latency infrastructure for real‑time model inference, including KV store and vector databases
Define and enforce observability standards for ML systems, including model performance monitoring, drift detection, capacity planning, and pipeline health metrics
Participate in on‑call rotation, leading incident response and root‑cause analysis for critical ML training and serving infrastructure
Partner with data scientists and ML engineers to improve platform usability, accelerate model iteration, and implement strong MLOps and SRE best practices
Champion operational excellence across ML infrastructure through automation, resilience engineering, disaster recovery planning, and continuous improvement
We’re excited if you have
BS or MS in Computer Science, Engineering, or a related quantitative field
8+ years of experience in DevOps, SRE, or ML infrastructure, including 4+ years supporting large‑scale ML or AI systems
Strong programming skills in Python, and/or Scala, or Java for platform automation and tooling
Deep experience with Kubernetes and container orchestration on GCP (GKE) and/or AWS (EKS)
Expertise with NoSQL or low‑latency data stores such as Aerospike or similar technologies
Hands‑on experience with data and orchestration technologies such as Apache Spark, Apache Flink, Apache Airflow, and Kafka
Experience building and maintaining CI/CD systems using tools such as Jenkins or GitLab Runner
Familiarity with feature engineering platforms such as Chronon and model lifecycle tools such as MLflow
Strong infrastructure‑as‑code experience with Terraform or similar tooling
Experience with observability platforms such as Prometheus, Grafana, and Datadog
Excellent communication and cross‑functional collaboration skills
Experience in the Advertising domain is a plus
Our Hybrid Work Approach Roku fosters an inclusive and collaborative environment where teams work in the office Monday through Thursday. Fridays are flexible for remote work except for employees whose roles are required to be in the office five days a week or employees who are in offices with a five‑day in‑office policy.
Benefits Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401 k/pension). Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs. It’s important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter.
Accommodations Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to EmployeeRelations@Roku.com.
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  • San Jose, Arizona, United States

Sprachkenntnisse

  • English
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