Founding DevOps / Systems / ML Ops Engineer - Physical AI Startup

Founding DevOps / Systems / ML Ops Engineer - Physical AI Startup Location: San Francisco, CA (you could work from home up to 2x/week) The company’s product involves physical AI, spatial intelligence, and multimodal LLMs. It is making real world infrastructure (like airplanes, trains, automobiles, the global supply chain, etc.) more efficient, safe, and stable. The company has 12 employees and 5 engineers, and is planning on hiring 6-10 people (including 3-5 engineers) in the next year. The company has raised seed funding and is in process of closing series A in early 2026. This is an opportune time to join since it would be shortly before the series A round closes, which would translate to more favorable equity, including founder shares which are stock grants rather than stock options. In this position, you would ideally be spending about 50% of your time on devops and 50% of systems engineering; it could skew in either direction depending on your preference and skills. Things you'd be working with include AWS, Azure, their own data center, Python, Kubernetes, infrastructure and automation design and strategy, AI, computer vision, video pipeline operations, systems and networking, CI/CD and deployment, and reliability and monitoring. The company will pay up to $200k in salary, plus equity which could be lucrative. Job Responsibilities Driving the design and implementation of automated infrastructure deployment and validation workflows supporting AI and computer vision initiatives. Designing, optimizing, and managing infrastructure for ingesting, processing, and analyzing real-time video streams at scale, ensuring high throughput, low latency, and reliability. Managing high-performance Linux environments and architecting complex networking configurations across cloud and edge systems to enable secure, reliable video data transmission. Building and orchestrating resilient Kubernetes-based environments while integrating diverse services and software components across the platform. Designing and maintaining sophisticated CI/CD pipelines, including automating infrastructure provisioning, deploying microservices with Helm, and integrating security scans and static code analysis tools. Building comprehensive monitoring systems and automated alerting mechanisms tailored for AI and video workloads. Diagnosing and resolving complex build failures and production issues related to infrastructure, system resources, and network performance. Collaborating closely with machine learning engineers to ensure validation readiness for new models and scaling enterprise deployment workflows across the organization. Qualifications Highly motivated and passionate professional with deep expertise in DevOps, automation engineering, and infrastructure orchestration. Strong track record of technical execution, complex systems integration, and successful cross-team collaboration. A BS, MS, or PhD in Computer Science or a related equivalent field. At least 3 years of applicable industry experience in DevOps or Systems Engineering. Expert-level knowledge of Linux administration. Strong background in CI/CD toolchains (e.g., Jenkins, GitLab CI, ArgoCD) and Infrastructure as Code (e.g., Terraform, Ansible). Nice to have Kernel tuning, and system performance debugging. Strong understanding of networking protocols (TCP/IP, UDP, DNS, VPNs, firewalls) and container networking challenges (CNI, service mesh). Proven experience managing infrastructure for video streaming (e.g., RTSP, HLS, WebRTC) or similarly high-throughput, real-time data pipelines. #J-18808-Ljbffr Skyrocket Ventures