🛠 Tech Stack

💼 About This Role

You'll lead the deployment of machine learning models into customer production environments, working alongside data scientists and simulation engineers. You'll own the scoping and architecture of data/ML systems, defining success metrics and delivery plans. This role offers the chance to work on-site with customers across advanced industries like aerospace and defense.

🎯 What You'll Do

• Own deployment of ML models to customer production environments
• Communicate results and trade-offs to senior stakeholders
• Lead scoping and architecture design for data/ML systems
• Mentor and develop engineers and data scientists
• Travel to customer sites for 3-4 weeks per quarter

📋 Requirements

• 3+ years industry experience (post Masters or PhD) in commercial environment
• End-to-end ML system design and deployment experience
• Python proficiency with PyTorch, Pandas, fastAPI, Scipy, Kubeflow
• US citizenship due to aerospace/defense work

✨ Nice to Have

• Experience with 3D point-cloud and mesh data
• Background in CAE/CFD/FEA or physics simulation
• Experience with customer-facing technical roles

🎁 Benefits & Perks

• 📈 Equity options - share in company success
• 💰 5% 401(k) contribution
• 🏖️ 20 days annual leave + public holidays
• 👶 Enhanced parental leave (3mo paternity, 6mo maternity)
• 🍽️ Free team lunch 1x/week

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Onsite Interview· 180 min

🚩 Heads Up

• Significant travel required (3-4 weeks per quarter)
• Role requires US citizenship, limiting candidate pool