Software Engineer - Infrastructure
Baseten - San Francisco, California, United States, New York, Remote
Posted Mar 9, 2025
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- 401(k) match
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Schedule
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- Weekend work
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About this role
Software Engineer - Infrastructure San Francisco, California, United States, New York, Remote 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 $300M Series E , backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to 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 - Inference on B200 GPUs - Multi-node inference - 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
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