Senior/Staff Software Engineer - Platform

VoxelSan Francisco, CA
104d

About The Position

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.

Requirements

  • Bachelor's degree in Computer Science, Software Engineering, or a related technical field (or equivalent experience)
  • 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

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
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