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Voxel is transforming workplace safety and operational efficiency through AI-driven computer vision technology. The company's platform helps Fortune 500 safety and operations leaders uncover root causes, drive proactive risk reduction, and make data-driven decisions.
You will join the perception team as a senior engineer responsible for turning raw video into reliable, customer-facing incidents. The team is re-architecting the perception system around stream-based processing, and you will take research-grade computer vision techniques and make them work in production: scalable, observable, and integrated cleanly into the wider product. You will be a technical leader on the team, setting direction through design and execution rather than people management.
Key responsibilities:
- Convert 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 the stream-processing architecture (Flink/PyFlink), working with the platform team on model serving, configuration management, and orchestration
- Own and improve production computer vision models, including training, evaluation, and inference optimization (Triton, TensorRT, multi-backend serving)
- Design logic that converts model outputs into trustworthy incidents: tracking, filtering, probabilistic reasoning, and state machines
- Build observability into all shipped work: metrics, dashboards, and evaluation loops that show whether a model or pipeline is working in the field
- Reduce end-to-end latency and cost while maintaining detection quality
- Partner with go-to-market, customer success, and data operations teams to plan customer rollouts, tune deployments, and improve labeling and review quality
- Evaluate and integrate third-party ML tooling (orchestration, labeling, dataset curation) and drive adoption across the team
- Write clear design documents and requirements, and de-risk major changes with proofs of concept
You will have real influence over the architecture of a system being rebuilt, with a direct line from your work to customer outcomes. The role emphasizes technical leadership without authority, ownership beyond model development, pragmatism about production readiness, mentorship of teammates, and comfort with architectural ambiguity.
REQUIREMENTS:
- 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
Nice to have:
- Experience with the full computer vision data lifecycle: collection, sampling, labeling, and curation
- Experience with auto-labeling or embedding-based data search
- Exposure to customer deployments or field-facing ML systems
