Full-Time
ML Ops / DevOps Engineer
Zensors
11-50 employees
AI-powered video analytics for physical spaces
No salary listed
San Francisco, CA, USA
In Person
Bachelor's, Master's, PhD
 DevOps & Infrastructure (1) |
|---|
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- A BS, MS, or PhD in Computer Science or a related equivalent field.
- At least 4 years of applicable industry experience in DevOps, MLOps, or Systems Engineering.
- Expert-level knowledge of Linux administration, kernel tuning, and system performance debugging.
- Strong understanding of networking protocols including TCP/IP, UDP, DNS, VPNs, firewalls, and container networking challenges such as CNI and service mesh.
- Proven experience managing infrastructure for video streaming, such as RTSP, HLS, or WebRTC, or similarly high-throughput, real-time data pipelines.
- Deep expertise in Kubernetes, including cluster management, Helm charts, and orchestration.
- A strong background in CI/CD toolchains such as Jenkins, GitLab CI, or ArgoCD.
- Proficiency in infrastructure-as-code tools such as Terraform or Ansible.
- Experience working in NixOS environments, declarative package management, and virtualization environments is highly required.
- Drive the design and implementation of automated infrastructure deployment and validation workflows supporting AI and computer vision initiatives.
- Design, optimize, and manage infrastructure for ingesting, processing, and analyzing real-time video streams at scale.
- Maintain high-performance Linux environments.
- Architect and troubleshoot complex cloud and edge networking configurations for video data transmission between physical cameras, processing nodes, and the cloud platform.
- Create resilient automation pipelines and orchestrate Kubernetes-based environments.
- Ensure the integration of diverse machine learning and software components.
- Design CI/CD pipelines.
- Automate infrastructure provisioning, potentially including bare-metal-to-Kubernetes bring-up.
- Deploy microservices using Helm.
- Integrate security scans and static code analysis tools into the workflow.
- Build monitoring systems and automated alerting mechanisms for intensive AI and video workloads.
- Diagnose and resolve complex build failures and production issues related to system resources or network bottlenecks.
- Collaborate with machine learning engineers to ensure validation readiness for new models.
- Take ownership of scaling enterprise deployment workflows across the organization.
Zensors uses an AI-powered spatial intelligence platform to convert existing hardware like CCTV cameras into smart sensors for large physical spaces. It analyzes video data and other inputs to deliver real-time and historical metrics, answers in plain English, and provides dashboards, alerts, and reports, with options to run in the cloud or on-premises. The service differentiates itself by leveraging current infrastructure rather than mandating new sensors, offering flexible deployment, and delivering anonymized analytics for environments such as airports, transit systems, retail, and corporate facilities. Its goal is to help operators optimize staffing, resources, safety, customer experience, and monetization through data-driven decisions.
Company Size
11-50
Company Stage
Seed
Total Funding
$130K
Headquarters
San Francisco, California
Founded
2018
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Simplify's Take
What believers are saying
- Boston Logan already uses Zensors across checkpoints for official TSA Real Time Wait Time.
- Harry Reid International deployed Zensors across 500 cameras, proving fast, low-capex rollouts.
- Toronto Pearson's wait times fell from 30 minutes to under six, strengthening sales proof.
What critics are saying
- Zensors depends on airport and TSA budgets; one procurement pause hits growth immediately.
- Competitors like RetailNext, Clarifai, and Palo Alto-backed vendors squeeze enterprise video analytics deals.
- A failed TSA rollout or privacy backlash would cripple its airport wedge and investor narrative.
What makes Zensors unique
- Zensors turns existing airport cameras into real-time operational sensors, without new hardware purchases.
- Its June 4, 2026 TSA contract validates Hologram as a national airport standard.
- Microsoft Azure co-sell status on June 3, 2026 eases enterprise procurement and deployment.
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Growth & Insights and Company News
6 month growth
↓ -4%1 year growth
↓ -4%2 year growth
↓ -4%Zensors AI has partnered with the Transportation Security Administration to deploy its Physical AI platform across US airport security checkpoints, automating passenger throughput data capture and enabling real-time wait time predictions. The platform, called Hologram, uses existing security cameras and AI to track processes including bag screening times, passenger processing rates and search rates. The system provides TSA headquarters with live operational views across airports and automates actions such as opening security lanes and allocating staff to reduce wait times. Boston Logan International Airport is amongst the first to deploy the platform at all checkpoints, displaying the official "TSA Real Time Wait Time" mark. Several other major airports are working with Zensors to roll out the solution nationwide.
MIAMI, May 29, 2024 /PRNewswire/ -- The Cities Today Institute is proud to announce the formation of an AI Adoption Alliance dedicated to advancing the integration of artificial intelligence (AI) technologies within the aviation industry alongside founder members Zensors AI, NVIDIA and AWS.Leading industry players join forces to establish an alliance to accelerate AI adoption in aviationThe alliance aims to create and disseminate understanding and best practices across the aviation community regarding AI developments and adoption, addressing critical subjects such as data governance, integration with legacy systems, accuracy and reliability, standardization, regulatory compliance, use case evaluation, and change management among many others.The alliance was launched today during the Airport Leadership Forum in Miami on May 29, 2024 with representation from multiple leading North American airport authorities.Driven by the exponential interest in AI capabilities and use cases within airports, this initiative marks a significant milestone in the realm of large multi-modal AI adoption and its applications in mission-critical industries. Airports, as vital nodes in global transportation networks, stand to benefit immensely from the implementation of specialized Foundation AI models trained with industry-specific data and spatial intelligence offering end-to-end situational awareness, facilitate collaboration across stakeholders, and enable accurate decision-making, planning, and disruption management support."Gen AI and Foundation AI models unlock a multitude of use cases within airport environments, providing stakeholders with unprecedented access to critical data and insights," said NVIDIA spokesperson. "This accessibility facilitates more effective collaboration and interaction with third-party entities such as airlines, operations teams, concessionaires, and other key stakeholders."The alliance will consist of a wide array of subcommittees covering all airport processes touching passenger experience, airside, terminal operations, and the adjacent airport ecosystem. Additionally, the group will harness subject matter expertise in areas such as data governance, technical evaluation, and driving proof of value initiatives across the airport community."As AI continues to rapidly develop and dominate the technology conversation, collaboration between business leaders and IT is critical. This alliance will assist with not only understanding the impact AI can have on the airport ecosystem, but more importantly, how to best integrate it with existing data systems and build adoption," said Paul Puopolo, EVP Innovation DFW Airport and CTI Airports President.By leveraging the collective expertise of the airport community and resources of Cities Today Institute, Zensors AI, AWS, NVIDIA, and other industry partners, the AI Adoption Alliance aims to accelerate the adoption of AI technologies within airports, enhance operational efficiency, improve passenger experience, and drive innovation across the aviation ecosystem."The Cities Today Institute supports community leaders' work to design and implement policies, strategies and projects by providing the necessary forums to harness collaboration and knowledge sharing. We are thrilled to jumpstart this important initiative for the airport community," said Bob Bennett, Chair of the Cities Today Institute."Zensors AI's mission is to empower mission-critical industries with cutting-edge AI solutions driving tangible improvements across their business performance and pioneering the intelligence-as-a-service market
CMU spinoff Zensors is opening up their artificial intelligence to aid in the fight against COVID-19.