Computer Vision Engineer

📋 Description

• Train and evaluate segmentation/classification/mass-estimation models for Mill Commercial camera
• Optimize edge models for production; scale ML pipeline with end-to-end lineage tracking
• Create and curate customer-specific datasets to support accuracy across foods and environments
• Analyze failure cases to drive data/model decisions
• Build annotation tools and ground-truth workflows including foundation-model labeling
• Collaborate with MLOps/edge on training, versioning, and deployment tradeoffs

🎯 Requirements

• Strong fundamentals in computer vision and deep learning
• Fluency with VLMs, LLMs, foundation models, and agentic systems
• Experience evaluating ML models with metrics and eval harnesses
• Product-shipping experience; production readiness, drift, and latency considerations
• Bias for action; ship experiments and learn quickly
• Experience building build-vs-buy decisions backed by data or a rubric