Design and operate scalable infrastructure and automation for real-time video ML workloads. Build Kubernetes orchestration, CI/CD pipelines, IaC, monitoring, and high-performance Linux/networking systems for cloud and edge deployments, collaborating with ML engineers to validate and scale model deployments.
Zensors is the spatial intelligence platform for the physical world. Our AI platform provides real-time insights—from airport queue times to office utilization—helping organizations make smarter operational decisions. Zensors processes massive streams of video data 24/7 with human-level accuracy. To do this at scale, we rely on cutting-edge optimization to ensure our vision transformers and spatial models run efficiently on both cloud and edge compute resources. Learn more at www.zensors.com.
As an ML / DevOps Engineer, you will play a pivotal role in advancing our infrastructure, scaling enterprise deployment workflows, and refining automation architectures to enable rapid iteration across the organization. You will sit at the critical intersection of machine learning and systems engineering. This role requires deep technical expertise not just in cloud-native tools, but also in the foundational Linux systems and networking required to process high-throughput video data reliably and securely across both cloud and edge environments.
- Infrastructure & Automation Strategy: Drive the design and implementation of automated infrastructure deployment and validation workflows supporting our cutting-edge AI and computer vision initiatives.
- Video Pipeline Operations: Design, optimize, and manage the infrastructure specifically tailored for ingesting, processing, and analyzing real-time video streams at scale. You will ensure high throughput, low latency, and rock-solid reliability for critical CV workloads.
- Systems & Networking Core: Maintain a strong systems foundation by managing high-performance Linux environments. You will architect and troubleshoot complex networking configurations (both cloud and edge) necessary for seamless video data transmission between physical cameras, processing nodes, and the cloud platform.
- Kubernetes & Orchestration: Create resilient automation pipelines, orchestrate complex Kubernetes-based environments, and ensure the seamless integration of diverse ML and software components.
- CI/CD & Deployment: Design sophisticated CI/CD pipelines. Your scope will include automating infrastructure provisioning (potentially bare-metal-to-Kubernetes bring-up), deploying microservices utilizing Helm, and integrating security scans and static code analysis tools into the workflow.
- Reliability & Monitoring: Build comprehensive monitoring systems and automated alerting mechanisms tailored specifically for intensive AI/video workloads. Diagnose and resolve complex build failures and production issues related to system resources or network bottlenecks.
- Collaboration & Scaling: Collaborate deeply with Machine Learning engineers to ensure validation readiness for new models, and take ownership of scaling enterprise deployment workflows across the entire organization.
Ideal Background & Qualifications
- Education: A BS, MS, or PhD in Computer Science or a related equivalent field.
- Experience: 6+ years of applicable industry experience in DevOps, MLOps, or Systems Engineering.
- Professional Profile: You are a highly motivated professional with a strong track record of technical execution, complex systems integration, and successful cross-team collaboration.
- Systems & Networking Mastery: Expert-level knowledge of Linux administration, kernel tuning, and system performance debugging. Strong understanding of networking protocols (TCP/IP, UDP, DNS, VPNs, firewalls) and container networking challenges (CNI, service mesh).
- Data & Video Pipelines: Proven experience managing infrastructure for video streaming (e.g., RTSP, HLS, WebRTC) or similarly high-throughput, real-time data pipelines.
- Cloud-Native & CI/CD: Deep expertise in Kubernetes (managing clusters, Helm charts, orchestration) and a strong background in CI/CD toolchains (e.g., Jenkins, GitLab CI, ArgoCD).
- Infrastructure as Code: Proficiency in IaC tools (e.g., Terraform, Ansible).
- Specialized Environments: Experience working in NixOS environments, declarative package management, and virtualization environments is highly required.
What We Offer
- Competitive base salary + equity options.
- Comprehensive health, dental, and vision benefits.
- The rare opportunity to build the infrastructural backbone for a pioneering platform in Physical AI and computer vision.
Similar Jobs
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
The role involves designing and implementing advanced analytics solutions for healthcare payers, analyzing complex problems, mentoring juniors, and building client relationships.
Top Skills:
AzureDatabricksGitMl-OpsPython
Digital Media • Gaming • Information Technology • Software • Sports • Esports • Big Data Analytics
Support and optimize outsourced customer experience operations by partnering with vendors and internal teams. Monitor performance metrics, review interactions, drive continuous improvement, facilitate calibrations and escalations, and coordinate cross-functional responses to protect service levels and customer satisfaction.
Top Skills:
Google WorkspaceMS Office
Digital Media • Gaming • Information Technology • Software • Sports • Esports • Big Data Analytics
Design and scale distributed, high-availability systems and platform architectures. Define frameworks, tooling, and standards, contribute hands-on to prototypes and production, guide teams on reliability, observability, and operational excellence, and align technical decisions with product and business priorities.
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
