Role overview
MLOps Engineer – Data Center Customer Engineering | San Diego, California | $108,300 - $162,500
We're working with a global leader in next-generation AI hardware and high-performance semiconductor innovation on this exciting opportunity. Join a elite team at the forefront of the generative AI revolution, where you will bridge the gap between cutting-edge AI silicon and massive data center deployments.
As an MLOps Engineer, you will lead the orchestration and optimization of rack-scale deep learning workloads powered by industry-leading AI inference accelerators. This is a high-impact role involving hands-on systems engineering, infrastructure-as-code automation, and the scaling of complex AI pipelines for strategic global partners.
The Role
- Lead the deployment, provisioning, and lifecycle management of end-to-end deep learning inference pipelines using advanced Cloud AI accelerators.
- Architect and maintain robust Infrastructure-as-Code (IaC) tools to automate rack-scale management software and server orchestration.
- Manage high-performance physical infrastructure including servers, storage, networking, and direct hardware-accelerated AI components.
- Ensure maximum uptime through proactive monitoring, incident response, and root cause analysis across massive data center clusters.
- Interface directly with strategic customers to optimize performance metrics, KPIs, and SLAs for energy-efficient generative AI and computer vision workloads.
What you'll work on
- 2+ years of professional experience in Software Engineering or MLOps (or a Master's degree with 1+ year or a PhD).
- Expert proficiency in Python, Bash, or C++ for automation, scripting, and systems-level debugging.
- Hands-on experience with Linux environments, bare-metal deployments, and virtualization platforms.
- Deep understanding of AI/ML inference workloads and the physical infrastructure required to support them (Servers, Networking, AI Accelerators).
- Familiarity with Data Center Infrastructure Management (DCIM) tools and environmental monitoring systems.
Tags & focus areas
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