🛠 Tech Stack

💼 About This Role

You'll lead development of physics-informed predictive maintenance systems for high-value industrial equipment. You'll build pipelines fusing inspection imagery with operating history to predict remaining component life. This role combines deep computer vision expertise with direct customer collaboration.

🎯 What You'll Do

• Select and fine-tune pretrained vision encoders for industrial imaging
• Apply gradient-based interpretability methods for model review
• Build joint models combining visual features with tabular and time-series data
• Develop probabilistic output models with calibrated uncertainty quantification

📋 Requirements

• Deep expertise in computer vision and pre-trained encoders (ViT, DINOv3, ResNet)
• Strong command of gradient-based interpretability methods (Grad-CAM, integrated gradients)
• Proven ability to build joint models fusing visual and heterogeneous inputs
• Experience with production ML pipelines in enterprise cloud environments

✨ Nice to Have

• PhD or equivalent research experience in computer vision
• Physics-informed or hybrid ML approaches
• Domain experience in aerospace, energy, or heavy industry

🎁 Benefits & Perks

• 🚀 Equity options - share in company growth
• 💰 5% 401(k) contribution - build long-term security
• 🏥 Private health insurance - comprehensive cover
• 👶 Enhanced parental leave - 3 months paternity, 6 months maternity full pay
• ☀️ 20 days annual leave + public holidays

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Initial Phone Screen· 30 min
2. 2Technical Interview· 60 min
3. 3On-site Interview· Half day