Engineering
What you’ll do
- Own onboarding outcomes against success metrics and customer KPIs (quality, reliability, time-to-value)
- Execute the initial onboarding cycle using internal tools, then revisit and iterate to improve quality as new data and edge cases appear
- Validate input data quality and flag issues early (camera angle, occlusion, anonymization, variance, missing detections)
- Detect and document edge cases and SOP/process variance; grow a diverse dataset and keep it up to date
- Communicate progress, metrics movement, and blockers clearly to stakeholders; propose concrete next steps
- Improve the onboarding process over time: checklists, docs, templates, and suggestions for tool improvements based on real usage
- Coordinate with installation teams to ensure camera setups support reliable onboarding and cross-station consistency
You are
1. 2–5 years experience in a structured execution role (implementation, QA, solutions engineering, ops/industrial engineering, data ops, etc.)
2. Metrics-minded: you can define “good”, track it, and drive iteration until it improves
3. Detail-oriented and reliable with process execution (no skipped steps, good documentation hygiene)
4. Fast, concise communicator who escalates early and clearly
5. Strong ownership mindset: you drive onboarding to completion and keep improving it post go-live
6. Comfortable with technical systems (ML depth not required, but you can reason about symptoms and inputs)