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Job Requirements of Sr Software Engineer:
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Employment Type:
Full-Time
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Location:
Palo Alto, CA (Onsite)
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Sr Software Engineer
Bayone Solutions Inc
Palo Alto, CA (Onsite)
Full-Time
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 programing languages
Knowledge of best practices for scalability, reliability, and security
Understanding of DevOps 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)
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 programing languages
Knowledge of best practices for scalability, reliability, and security
Understanding of DevOps 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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