Staff Machine Learning Operations Engineer - Computer Vision
Core
Own the production MLOps infrastructure for BrakeWise, a mobile computer vision app that inspects brake pads and rotors in real-time for automotive service shops.
Role type
Staff MLOps Engineer (Computer Vision)
Builds
Scalable, low-latency inference pipeline for segmentation and classification models serving live service technicians.
Domain
Automotive service / Computer Vision / Cloud Infrastructure
Deliverable
production ML models
Required skills
multi-stage CV pipeline architecture, GCP cloud infrastructure, model serving optimization, CI/CD for ML, data labeling workflows, drift detection, on-call incident response
Preferred skills
on-device/edge inference, active learning, robotics/IoT integration, automotive service domain knowledge
Technologies
GCP (Vertex AI, Cloud Run, GKE, Pub/Sub), Python, PyTorch/TensorFlow, Triton, TorchServe, ONNX, TensorRT, Terraform, GitHub Actions
Responsibilities
Re-architect MVP pipeline to scalable containerized/GPU-backed serving; own model deployment, versioning, and rollback; build improvement loops with field data collection and evaluation harnesses; monitor production quality and define commercial metrics; optimize model performance and evaluate on-device vs cloud trade-offs; establish MLOps foundations and serve as cloud architecture counterpart.
Seniority
Staff, hands-on IC with architectural leadership
