Infrastructure Software Engineer
Posted Updated
- 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
