Teams at Outpost

Own computer-vision accuracy end-to-end: measure per-customer metrics, investigate misclassifications, curate and label datasets, prioritize retraining, and build continuous learning pipelines. Partner with ML/CV engineers and stakeholders to define acceptance criteria, translate findings into actionable fixes, and eventually implement tooling and retraining to ship regular model improvements.

Build end-to-end production features across backend, frontend, and database. Integrate LLM APIs and agentic workflows into products and internal developer tools. Improve CI/CD, deployment, and developer infrastructure. Debug production issues on GCP and containerized services; participate in code reviews and architecture discussions on a small collaborative team.

Own and improve uptime for backend services, APIs, workers, and ML pipelines; build monitoring, alerting, auto-remediation, optimize GCP infrastructure and Postgres performance, run on-call rotation and blameless postmortems.