Hybrid Senior/Staff Software Engineer - Platform

at Voxel

• Job title: Senior/Staff Software Engineer - Platform
• Job type: Full Time
• Experience level: Senior
• Salary: $190,000 - $250,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Distributed Systems, Google Cloud Platform, GRPC, Kafka, Kubernetes, Microservices, Terraform
• Location requirements: Hybrid, San Francisco, United States

About the role

• Senior Software Engineer designing and building core components of Voxel’s perception and computer vision systems. Leading development of distributed systems and collaborating with cross-functional teams.

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

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

Benefits

• Health insurance
• 401(k) matching
• Flexible work arrangements
• Professional development opportunities