🛠 Tech Stack

💼 About This Role

You'll build the data engine for training perception models and optimize ML pipelines on edge and cloud. You'll own the full lifecycle from edge inference to cloud retraining, ensuring ML models improve continuously for critical applications.

🎯 What You'll Do

• Construct optimized data pipelines to run ML models
• Evolve data engine architecture to scale high-fidelity labels
• Integrate foundation models (LLMs, VLMs) for labeling and QA
• Leverage software-in-the-loop and hardware-in-the-loop testing

📋 Requirements

• 5+ years of relevant work experience in ML infrastructure
• Familiarity with modern ML infrastructure and data-centric AI
• Experience creating or working on microservices and/or databases
• U.S. citizenship and eligibility to obtain a security clearance

✨ Nice to Have

• Full-stack experience with React, TypeScript, Python, Golang
• Experience with Docker, Kubernetes, Opensearch, Postgres
• Direct experience with foundation models for data automation

🎁 Benefits & Perks

• 🏖️ Paid Time Off
• 🏥 Comprehensive health, dental, vision insurance
• 📚 Learning and wellness stipends
• 💰 Equity in the form of options and RSUs
• 🏦 401k retirement benefits with employer match

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Screen· 60 min
3. 3Onsite Interviews· 4 hours