Job Overview
Location
San Francisco
Job Type
Full-time
Category
Software Engineering
Date Posted
May 22, 2026
Full Job Description
đź“‹ Description
- • Design and own end-to-end network architecture for data center clusters powering GPU-based AI inference and training systems.
- • Define cluster fabric architectures using InfiniBand or high-performance Ethernet protocols to optimize throughput and reduce latency for distributed workloads.
- • Design and implement spine-leaf topologies and rack-level connectivity for scalable, high-availability data center networks.
- • Select and specify switches, optics, and cabling systems based on performance, reliability, and scalability requirements for GPU clusters.
- • Lead network bring-up, validation, and performance testing across new and existing data center deployments.
- • Partner closely with hardware and platform engineering teams to align network design with system-level performance goals.
- • Define and document standardized network deployment practices to ensure consistency across multiple data center sites.
- • Perform ongoing network performance tuning to support demanding AI workloads, including RDMA and low-latency communication protocols.
- • Own technical decision-making for network infrastructure at a staff level, with direct impact on model training and inference efficiency.
- • Mentor and support junior engineers and future team members as the network team scales.
- • Collaborate with cross-functional teams to troubleshoot complex network issues affecting distributed AI systems.
- • Contribute to the evolution of network standards and best practices for high-performance computing environments.
- • Ensure network infrastructure meets the reliability and performance demands of mission-critical AI applications used by leading ML companies.
- • Maintain detailed documentation of network configurations, topology diagrams, and operational procedures.
- • Participate in on-call rotations to respond to critical network incidents affecting production AI infrastructure.
🎯 Requirements
- • Experience designing and operating data center or HPC networks.
- • Strong familiarity with InfiniBand, RDMA, or high-performance Ethernet.
- • Strong hands-on skills in network configuration, debugging, and performance tuning.
- • Experience owning complex systems end-to-end at a senior level.
- • Experience leading technical projects or cross-functional efforts.
- • Prior leadership or mentoring experience is a plus.
🏖️ 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 (offices 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.
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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