Voxel is a site intelligence platform committed to helping organizations reduce safety and operational risk in industrial environments. Backed by Eclipse Ventures.
About the role
Turn research ideas (transformers, ensemble models, new detection and classification approaches) into production features, from prototype through evaluation, rollout, and iteration Design and build perception pipeline components on our stream-processing architecture (Flink/PyFlink), working with the platform team on model serving, configuration management, and orchestration Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 5+ years building and shipping production ML or computer vision systems, with a track record of moving techniques from research to reliable product
- Strong Python, working knowledge of C++ or Go is a plus
- Experience with model serving and inference optimization (Triton, TensorRT, or similar)
- Experience with streaming or distributed data processing (Flink, Kafka, or similar)
- Solid grounding in evaluation: building datasets, defining metrics, and detecting regressions before customers do
- Familiarity with Kubernetes, Docker, and infrastructure as code (Terraform, ArgoCD), AWS experience
More about this role
Industrial labor powers our world and protecting the people who do that work is both a moral imperative and a business advantage. At Voxel, we're transforming workplace safety and operational efficiency through AI-driven computer vision technology that helps organizations see unseen risks before incidents occur.
Voxel's platform enables Fortune 500 safety and operations leaders to uncover root causes, drive proactive risk reduction, and make smarter, data-driven decisions. Our Solutions Engineering team ensures customers successfully adopt, deploy, and scale Voxel across complex enterprise environments.
About the role
Our perception team turns raw video into reliable, customer-facing incidents. We're re-architecting our perception system around stream-based processing, and we need an engineer who can take research-grade computer vision techniques and make them work in production: scalable, observable, and integrated cleanly into the wider product. You'll be a technical leader on the team, setting direction through design and execution rather than people management.
Turn research ideas (transformers, ensemble models, new detection and classification approaches) into production...
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