🛠 Tech Stack

💼 About This Role

You'll lead architecture and delivery of large-scale ML platform capabilities including training, deployment, and observability systems. You'll drive the design of distributed systems for data processing and model lifecycle management. This role shapes tech strategy at the intersection of ML infrastructure and distributed systems engineering.

🎯 What You'll Do

• Design and evolve ML platform architecture for training, deployment, and observability
• Scale distributed systems for data processing and model lifecycle management
• Lead incident response and implement long-term system improvements
• Mentor engineers and establish best practices for ML system design

📋 Requirements

• 6–8+ years of experience in software engineering or ML infrastructure
• Advanced proficiency in Python and production software engineering
• Experience leading cross-functional technical initiatives across multiple teams
• Experience with model deployment, inference systems, and observability frameworks

✨ Nice to Have

• Experience with Kubernetes and ML orchestration tools
• Familiarity with data lineage systems and ML-ready data representations
• Background in graph, geometry, or multimodal data

🎁 Benefits & Perks

• 💰 Competitive salary ranging from $152k to $272k
• 📈 Annual cash bonus plus stock grants
• 🏥 Comprehensive health, dental, and vision insurance
• 🏖️ Flexible remote work across US and Canada
• 📚 Learning and development support for continuous growth

📨 Hiring Process

Estimated timeline: 3-5 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3System Design Interview· 60 min
4. 4Hiring Manager Interview· 45 min