over 1 year ago
Base Salary
$165k - $330k/yr
Responsibilities
- Develop infrastructure components for the ML inference platform using Python and Go.
- Implement and maintain Kubernetes deployments for model serving.
- Contribute to the 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 with team members to implement technical solutions.
- Balance performance optimization with system reliability.
- Participate in technical discussions about infrastructure improvements.
- Learn and apply infrastructure best practices.
Requirements
- Bachelor's degree or higher in Computer Science or a related field.
- Proficient coding abilities in one or more popular programming or scripting languages; Go proficiency is a plus.
- Working knowledge of Kubernetes and containerization.
- Basic understanding of machine learning concepts and model serving.
- Familiarity with distributed systems concepts.
- Experience with basic monitoring and logging tools.
- Interest in ML/AI infrastructure and willingness to learn.
- Strong collaboration and communication skills.
Benefits
- Competitive compensation including meaningful equity (amount not stated).
- 100% medical, dental, and vision insurance coverage for the employee and dependents.
- Flexible paid time off and 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 ML startups and learning 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.