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Senior Production Engineer

2 months ago

Remote, Oregon, United States 102 Yahoo Inc. Full time
About the Role

The Monetization Production Engineering team at 102 Yahoo Inc. is seeking an experienced DevOps/Cloud Infrastructure engineer with expertise in GCP and a strong knowledge of machine learning frameworks. The ideal candidate will be passionate about working in a dynamic environment and have the required skills to excel in this role.

Responsibilities
  • Manage large-scale distributed systems by analyzing existing processes and systems to identify areas of improvement.
  • Collaborate with the engineering team on the product roadmap and provide support in terms of capacity planning and scaling, operability review, monitoring and alerting, process optimization, security and compliance.
  • Work on challenging system and network problems to improve system performance and reliability.
  • Develop and maintain tools and frameworks for monitoring and logging of machine learning models in production.
  • Collaborate with data engineers to ensure efficient data ingestion, transformation, and storage for machine learning applications.
  • Participate in on-call rotation, identify and resolve technical issues that arise in the production environment by closely working with engineering teams or platform teams.
  • Stay updated with industry trends and best practices in DevOps, MLOps, and cloud technologies.
Requirements
  • BS/MS in Computer Science or equivalent degree.
  • At least 6+ years of experience in DevOps/PE/SRE and Software Development roles.
  • At least 2+ years of experience in containerization and orchestration technologies (e.g. Docker, Kubernetes), and Google Cloud Platform (GCP).
  • Intermediate level of coding expertise in one or more language including Java, Nodejs, Python, or Go.
  • Experience with Infrastructure-as-code tools (ex. Terraform).
  • Proven experience in designing and implementing machine learning infrastructure and pipelines.
  • Experience with data engineering tools and frameworks.
  • Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and model training workflows, deployment techniques.
  • Good knowledge of TCP/IP and networking.
Preferred Qualifications
  • Experience in designing, managing large-scale infrastructure in GCP, AWS EKS, AWS Open search, multi-zone, multi-region deployments.
  • Deep understanding of UNIX/Linux system internals and tools for troubleshooting application stack dumps and networking.
  • Experience working with GitHub Actions.
  • Experience with software-based load balancers like Ngnix.
  • Experience with system reliability tools like Open telemetry, Prometheus, Splunk, ELK.
  • Experience with storage solutions like REDIS, DynamoDB.
  • Experience in deploying and managing machine learning models in a production environment.
About Us

102 Yahoo Inc. is a leading technology company that connects brands and partners with a massive audience. We are committed to providing an inclusive and collaborative environment that encourages authenticity and fosters a sense of belonging. Our team is passionate about working in a dynamic environment and has a strong knowledge of machine learning frameworks.

Benefits

102 Yahoo Inc. offers a competitive compensation package, including a salary range of $128,000 to $266,875 per year, depending on factors such as location, skills, and experience. The package also includes incentive compensation opportunities in the form of discretionary annual bonus or commissions, in addition to equity incentives. We provide industry-leading benefits, including healthcare, 401K savings plan, company holidays, vacation, sick time, parental leave, and an employee assistance program. Eligibility requirements apply.

Work Environment

102 Yahoo Inc. has a high degree of flexibility around employee location and hybrid working. Most roles do not require specific regular patterns of in-person office attendance. If you join our team, you may be asked to attend (or travel to attend) on-site work sessions, team-building, or other in-person events. When these occur, you will be given notice to make arrangements.