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Sr Software Engineer

Job in Palo Alto, Santa Clara County, California, 94306, USA
Listing for: Bayone
Part Time position
Listed on 2026-07-01
Job specializations:
  • Software Development
    Cloud Engineer - Software, DevOps
Salary/Wage Range or Industry Benchmark: 120000 - 160000 USD Yearly USD 120000.00 160000.00 YEAR
Job Description & How to Apply Below

WHO ARE WE LOOKING FOR

We are looking for candidates who are willing to work with a team and passionate about building efficient tools and frameworks to support workloads of Enterprise AI and enable cutting-edge solutions for machine learning model development lifecycle. This is a hybrid role requiring your presence onsite 3 days per week, where you will report to an Engineering Manager.

RESPONSIBILITIES
  • Define architecture and its plan to build robust, scalable, distributed systems for Enterprise AI
  • Lead implementation of critical systems while maintaining reliability
  • Work with other teams to maximize infrastructure usage and build efficient solutions for heavy tasks
  • Collaborate with other teams in Woven by Toyota to integrate services in machine learning model development lifecycle
  • Work closely with teammates to establish and improve development standards
  • Implement CI/CD best practices for our services.
  • Analyze and monitor our services
  • Responding to incidents and taking on-call for systems in production
MINIMUM QUALIFICATIONS
  • Bachelor's degree in computer science or equivalent
  • Strong experience with Kubernetes in production and container technologies
  • Strong experience with event-driven, distributed, and cloud architectures
  • Experience with Python, Golang, or related programming languages
  • Knowledge of best practices for scalability, reliability, and security
  • Understanding of Dev Ops best practices
  • Ability to speak business-level English with a collaborative spirit for effective stakeholder partnerships
NICE TO HAVES
  • Experience with databases and blob storage
  • Familiarity with Kubeflow or Flyte
  • Production system management, monitoring, and analysis
  • Understanding of machine learning development life cycle
  • Working knowledge of cloud infrastructure (e.g., AWS, GCP)
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