
Job Overview
Location
San Francisco
Job Type
Full-time
Category
DevOps & SysAdmin
Date Posted
April 5, 2026
Full Job Description
đź“‹ Description
- • IT Support/Operations Engineer at BaseTen Inc., a rapidly growing AI infrastructure company powering mission-critical inference for leading AI firms. This role is critical in bringing technical support in-house to ensure a seamless, high-touch experience for all employees, directly impacting productivity and workplace experience.
- • Day-to-day responsibilities include serving as the escalation point for technical issues across Mac and Windows devices, managing user lifecycle (onboarding/offboarding), maintaining office IT infrastructure, managing IT assets and vendor relationships, supporting office buildouts, identifying automation opportunities, and performing systems administration tasks such as managing access controls and cloud service maintenance.
- • BaseTen is a fast-scaling AI infrastructure provider backed by top-tier investors, serving innovative AI companies. The company values in-person collaboration with a hybrid policy of three days per week in the San Francisco office to maintain high-performing physical office and AV systems.
- • In this role, you will gain hands-on experience scaling IT operations in a high-growth tech environment, develop expertise in enterprise MDM and identity systems, contribute to workplace technology strategy, and grow your impact through automation and process improvement while supporting cutting-edge AI innovation.
Skills & Technologies
About BaseTen Inc.
BaseTen provides a serverless, GPU-accelerated platform that lets machine-learning teams deploy, scale and monitor custom models behind autoscaling inference endpoints. The service abstracts infrastructure management, supports PyTorch, TensorFlow and Hugging Face artifacts, and offers built-in observability, A/B testing and fine-tuning. Customers integrate via REST or GraphQL APIs and pay only for compute used. Founded in 2019 and headquartered in San Francisco, BaseTen targets data scientists and product teams seeking production-grade ML serving without Kubernetes complexity.
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