Senior Architect, Computer Vision

In this Senior Architect role, you will own the architecture, training, and deployment of vision and vision-language models for Rockwell's FactoryTalk Analytics VisionAI and broader vision capabilities. You will shepherd practical, on-premises computer vision work that respects OT security constraints and integrates into customer plants. The position combines hands-on engineering with cross-team leadership to raise the group's baseline capabilities and reliability. You will shape the portfolio's vision and influence external engagements with a strong engineering focus.

• Health Insurance including Medical, Dental and Vision
• 401k
• Paid Time off
• Parental and Caregiver Leave
• Flexible Work Schedule

• Own model architecture, training, and evaluation for VisionAI and FactoryTalk portfolio
• Scale vision practices across the portfolio (dataset strategy, annotation pipelines, model selection, fine-tuning, quantization, edge deployment)
• Extend evaluation suites and release gates to measure accuracy, drift, and failure modes in deployments
• Serve as a CV/VLM subject-matter expert; review designs and mentor engineers
• Collaborate with Product Management and other architects on portfolio roadmap; clearly weigh cost, latency, and accuracy tradeoffs
• Design with OT constraints from the start: on-premises/disconnected inference, model provenance, data residency, IP protection
• Represent Rockwell's industrial vision perspective in customer engagements and external forums
• Pair with engineering teams to advance enterprise AI tooling and evaluation rigor

• Bachelor's degree or equivalent experience
• Legal authorization to work in the US (no visa sponsorship)
• Typically 8+ years of related experience
• Master's or PhD in Computer Vision, ML, Robotics, or related field (preferred)
• Experience training, evaluating, deploying CV models in production
• Proficiency with PyTorch or TensorFlow
• Familiarity with Industrial Control Systems
• Experience with vision-language models in practical tasks (VQA, scene/document understanding, multimodal retrieval)
• Edge AI platforms and inference optimization (NVIDIA Jetson, TensorRT, quantization, pruning, distillation)
• Experience with industrial/safety-relevant vision applications (quality inspection, OCR, robotic guidance, safety monitoring)
• Experience with synthetic data generation, digital twins, domain randomization
• Experience establishing MLOps for vision (dataset versioning, reproducible training, model registry, automated gates)
• Published CV or multimodal ML research/prototyping or open-source contributions

• Collaborative communication
• Mentoring and coaching
• Strategic thinking with portfolio impact
• Computer vision model architectures
• Vision-language models (VLM)
• PyTorch