Senior/Principal Platform Engineer

Responsibilities

• Own ML Platform as a product by defining requirements, writing RFDs, and shipping APIs, SDKs, CLIs, and UIs.
• Build and maintain the serving layer, model registry, pipeline orchestrator, and training and inference control planes.
• Set technical strategy and oversee scalable, reliable infrastructure with clear latency, availability, and cost objectives.
• Create paved-road templates, golden paths, opinionated defaults, and documentation to improve developer experience and time to production.
• Measure platform adoption, friction, reliability, and cost to prioritize the roadmap and validate outcomes.
• Partner with ML Engineering, Data Science, Infrastructure/SRE, Security, and Finance on performance, safety, and GPU-intensive workload costs.
• Develop tooling across the ML lifecycle and mentor engineers, lead design reviews, and drive cross-team architectural decisions.

Requirements

• 7+ years of professional experience and extensive system design experience building scalable, reliable platforms.
• Strong hands-on software engineering ability with experience shipping platform products and incorporating user feedback.
• Proficiency in API design and developer experience, including gRPC/REST APIs, SDKs, CLIs, and simple UIs.
• Experience with infrastructure-as-code and automation.
• Bachelor’s degree in Computer Science, Computer Engineering, Data Science, or a similar technical field.
• Experience with the end-to-end ML model lifecycle, including model serving, training, model CI/CD, and GPU resource management, is preferred.

Benefits

• Full-time employees are eligible for equity compensation and company benefits.
• Office-based roles are onsite Tuesday, Wednesday, and Thursday, with optional presence Monday and Friday.