Software Engineer - Infrastructure

Job details

Work model

Hybrid

Salary

Not listed by source

Location

San Francisco

Occupation

Software Developers(O*NET 15-1252.00)

What the role asks for

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE 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. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Infrastructure team: - Multi-cloud capacity management https://www.baseten.co/blog/how-baseten-multi-cloud-capacity-management-mcm-powers-cloud-self-hosted-and-hybr/ - Inference on B200 GPUs https://www.baseten.co/blog/accelerating-inference-nvidia-b200-gpus/ - Multi-node inference https://www.baseten.co/blog/how-multi-node-inference-works-llms-deepseek-r1/ - Fractional H100 GPUs for efficient model serving https://www.baseten.co/blog/using-fractional-h100-gpus-for-efficient-model-serving/ RESPONSIBILITIES - 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 REQUIREMENTS - Bachelor's degree or higher in Computer Science or 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 - 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to 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, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! 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. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

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