Senior Software Engineer - Platform
San Francisco, CA
Engineering /
Full Time /
Hybrid
Who Are We Industrial labor is incredibly dangerous work - almost 3 million people in the US per year are injured in the workplace for entirely preventable and at times, fatal or debilitating causes. Protecting these essential people who power our world is what motivates Voxelitos, and we'd love for you to join us. At Voxel, we're passionate about revolutionizing workplace safety and operations with groundbreaking, full-stack AI and computer vision technology.
Voxel’s site intelligence platform helps safety and operations leaders see the unseen risks, make strategic decisions, and prevent workplace incidents before they happen. Our customers include Fortune 500 companies across major grocers and retailers, manufacturers, food and beverage warehousers, supply chain and logistics service providers. Based in SF with team members sitting all over the globe, Voxel is backed by industry leading VC’s.
Voxel is seeking a highly skilled and experienced Senior Software Engineer, Platform to join our team. In this role you will design, build, and scale the core systems that power Voxel’s perception and computer-vision platform. The ideal candidate has a strong background in software engineering, extensive experience with distributed systems, and deep expertise in building and operating cloud-native infrastructure at scale.
Responsibilities:
Design, build, and scale core components of Voxel’s perception and computer vision systems, enabling real-time understanding of safety and operations in industrial environments
Lead the development of distributed systems for ingesting, processing, and analyzing video data across edge devices and cloud infrastructure
Develop secure, scalable backend services and APIs to power our video platform, including access control, data pipelines, and event detection services
Contribute to the architecture of low-latency, resilient services supporting real-time alerts, historical analytics, and ML inference workflows
Partner with ML engineers, product managers, and platform teams to deploy and operationalize machine learning models in production
Take ownership of key technical areas, influence design decisions, and mentor junior engineers when needed
Uphold engineering best practices in code quality, testing, monitoring, and operational excellence
Skills and Qualifications Must-Haves:
Bachelor's degree in Computer Science, Software Engineering, or a related technical field (or equivalent experience)
3–5 years of experience designing and building backend systems using REST/gRPC APIs, microservices, and containerized architectures
Proven track record of building and scaling distributed systems with real-time data processing using tools like Kafka, Flink, or Kinesis
Strong familiarity with deploying production systems in cloud environments such as AWS, GCP, or Azure
Experience using Kubernetes to deploy, scale, and manage containerized applications in production
Hands-on experience with infrastructure-as-code tools like Terraform or CloudFormation
Exposure to ML or computer vision pipelines, especially around data ingestion, preprocessing, or inference integration
Comfortable leading small technical projects or independently driving a component from design through deployment
