1 year ago
Base Salary
$165k - $330k/yr
Responsibilities
- Architect and develop infrastructure and platform features for self-hosted clusters, single-tenant environments, and cross-cloud workload orchestration
- Lead initiatives to productize secure and scalable private connectivity solutions
- Design solutions for regulatory, compliance, data residency, auditability, and enterprise data protection requirements
- Advance self-hosted infrastructure through capacity management, release management, and observability tooling
- Collaborate on secure, minimal Baseten deployments within partner environments
- Evaluate and implement virtualization technologies that improve platform isolation and security
- Write technical specifications, define product requirements cross-functionally, and drive projects through execution
- Mentor engineers and promote enterprise infrastructure best practices and knowledge-sharing
Requirements
- Bachelor's degree or higher in Computer Science or a related field
- 5+ years of experience building distributed systems, cloud infrastructure, or Kubernetes-based solutions in production environments
- Experience with enterprise security, compliance, and privacy requirements
- Advanced understanding of distributed systems, cloud architectures, and performance optimization
- Ability to independently manage technical projects from planning and specification through implementation
- Strong collaboration and communication skills, including cross-functional and customer coordination
- Preferred experience with AI/ML systems or familiarity with MLOps practices
Benefits
- 100% medical, dental, and vision insurance coverage for the employee and dependents
- Flexible PTO and a company-wide Winter Break from Christmas Eve through New Year's Day
- Paid parental leave
- Fertility and family-building stipend through Carrot
- Company-facilitated 401(k)
- Exposure to a variety of machine learning startups and networking opportunities
Tech Stack
Categories
About Baseten
Baseten builds an AI inference platform that provides tooling, infrastructure, and hardware to deploy, scale, and serve machine-learning models in production. The company sells managed model serving and developer tooling to software teams at AI product companies, with customers including Notion, Abridge, Writer, and Cursor. Privately held and headquartered in San Francisco, it focuses on high-availability, globally distributed inference for production workloads.