🛠 Tech Stack

💼 About This Role

You'll own ML Platform as a product, building APIs, SDKs, and UIs that enable hundreds of use cases and billions of inferences per day. You'll turn complex ML/AI infrastructure into clear, durable primitives for internal developers. This role blends product thinking, developer experience, and backend engineering at scale.

🎯 What You'll Do

• Own platform as a product and define requirements, write RFDs, ship APIs, SDKs, CLIs, and UIs
• Bootstrap and maintain core ML Platform components: Serving Layer, Model Registry, Pipeline Orchestrator
• Set technical strategy and oversee development of high-scale reliable infrastructure with clear SLOs
• Design great developer experiences with paved-road templates, golden paths, and opinionated defaults
• Instrument platform to measure adoption, friction, reliability, and cost; prioritize roadmap using data

📋 Requirements

• 5+ years professional experience with system design for scalable reliable ML platforms
• Proficiency in API design and developer experience (gRPC/REST, SDKs, CLIs, UIs)
• Experience with end-to-end ML model lifecycle including serving, training, model CI/CD, GPU management
• Bachelor's degree in Computer Science, Computer Engineering, Data Science, or similar technical field

✨ Nice to Have

• Hands-on ML experience
• Track record of building internal platforms that developers love

🎁 Benefits & Perks

• 💰 Equity compensation
• 🏥 Health benefits
• 🏢 Onsite office with hybrid flexibility (Tue-Thu in office, Mon/Fri optional)

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter screen· 30 min
2. 2Technical interview· 60 min
3. 3Onsite interviews· 4 hours