Contribute to the development and scaling of Voxel’s perception and computer vision systems, powering real-time understanding of industrial environments
Design and deploy distributed systems for video ingestion, processing, and inference across both edge devices and cloud infrastructure
Build and secure cloud APIs, access control systems, and backend services that support the video platform and data pipelines
Develop scalable and resilient services that enable low-latency event detection, real-time alerts, and historical video analytics
Collaborate with cross-functional teams—including ML engineers, product managers, and researchers—to bring computer vision models into production
Influence the team’s technical direction and uphold high standards in code quality, system design, and operational excellence

Bachelor’s degree in Computer Science, Software Engineering, or a related field (or equivalent experience)
0-2 years of experience developing backend systems using REST APIs, containerized services, and microservices architecture
Exposure to building and scaling distributed systems, with hands-on experience using Flink, Kafka, or Kinesis for real-time data processing
Familiarity with designing and delivering production-ready systems in a collaborative team environment
Working knowledge of infrastructure-as-code tools like Terraform and cloud platforms such as AWS, Azure, or GCP
Experience contributing to machine learning or computer vision pipelines, particularly around data ingestion or processing infrastructure
Practical experience using Kubernetes to deploy, monitor, and manage containerized workloads.

Software Engineer – Platform

Key skills