gpu-scheduling jobs in San Diego

Staff Engineer responsible for designing and implementing scalable test automation frameworks and infrastructure for machine learning systems across multiple engineering teams. The role requires expertise in validating ML pipelines across data, training, evaluation, deployment, and monitoring; testing GPU-accelerated workloads in Kubernetes; qualifying integrated hardware and software systems; and developing comprehensive integration and regression strategies.…See more Deep experience with Python automation, distributed systems testing, performance profiling, and observability is essential, along with strong system-design skills for complex, multi-tenant environments.

Senior Staff Engineer responsible for designing and building an MLOps platform that supports distributed AI training, reinforcement learning, and foundation model development at scale. You will architect Kubernetes-native infrastructure for GPU workloads, design self-service AI development workflows, manage the data and model lifecycle, and lead platform distribution across cloud, on-premises, and air-gapped environments.…See more The role requires deep expertise in modern AI frameworks (PyTorch, Hugging Face Transformers), distributed systems, GPU scheduling, and cloud-native infrastructure, with a focus on enabling researchers and engineers to move from experimentation to production rapidly.

Design, develop, and deploy a hybrid container/virtualization platform serving enterprise workloads across on-prem and cloud environments. Integrate core platform services (identity, PKI, DNS, logging, monitoring, secrets management) and support GPU-enabled AI/ML workloads.…See more Establish CI/CD pipelines, Infrastructure-as-Code automation, and standard operating procedures for configuration management, verification, and patch management. Lead cross-functional teams on containerization, DevSecOps, incident response, and ATO compliance efforts.