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Baseten

Infrastructure Software Engineer

Posted Updated
Discussion
  • As an Infrastructure Software Engineer at Baseten, you’ll build and maintain components of our ML inference platform that powers production AI applications
  • You’ll contribute to the core infrastructure, enabling developers to deploy, scale, and monitor ML models with high performance
  • Develop infrastructure components for our ML inference platform using Python and Go
  • Implement and maintain Kubernetes deployments for model serving
  • Contribute to our inference orchestration layer for model deployments
  • Build and enhance monitoring systems for model performance metrics
  • Implement efficient resource management solutions for ML workloads
  • Support infrastructure automation to improve ML deployment workflows
  • Work closely with team members to implement technical solutions
  • Help balance performance optimization with system reliability
  • Participate in technical discussions around infrastructure improvements
  • Learn and apply infrastructure best practices

Benefits

  • Remote-first work environment. The Baseten team is welcome to work from wherever they want; fully remote, in our San Francisco office, or a mix of both. Today, our team (including our founding team) is spread across the United States, Canada, and Armenia. We provide a $1,000 stipend for you to make your home-office comfortable and productive
  • Regular in-person team summits. We get together as a team three times a year to plan, workshop, and most importantly, get to know each other better
  • Unlimited PTO. We ask that everyone take at least 4 weeks of vacation. And we have a company-wide break between Christmas and New Year’s Day
  • Full healthcare coverage. Medical, dental and vision insurance for you and your family
  • Paid parental leave. 16-weeks fully paid parental leave (adoptive and non-birth parents included) and flexibility with schedules while returning to work
  • Company-sponsored 401(k) for you to contribute to
  • Learning and development budget. We encourage you to take classes, attend conferences, and invest in your craft and we’ll cover expenses to make it happen
  • Experience with basic monitoring and logging tools
  • Working knowledge of Kubernetes and containerization
  • Proficient coding abilities in one or more popular programming or scripting languages; Go proficiency is a plus
  • Familiarity with distributed systems concepts
  • Bachelor’s degree or higher in Computer Science or related field
  • Basic understanding of machine learning concepts and model serving
  • Interest in ML/AI infrastructure and willingness to learn
  • Strong collaboration and communication skills
  • If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you

Skills

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