Staff Software Engineer, Machine Learning Platform

What you'll do

• Own end-to-end architecture and system design for large, complex projects across the ML Platform.
• Define long-term technical strategy and direction for next-generation ML infrastructure and products.
• Design scalable architectures for model training, inference, feature stores, and LLM orchestration.
• Translate requirements from data scientists and product teams into functional, high-scale technical solutions.
• Arbitrate critical decisions regarding latency, reliability, cost, and security constraints.
• Lead cross-team initiatives to improve ML development velocity and MLOps maturity across the company.
• Mentor engineers and serve as a role model for designing and operating high-quality software systems.

What we're looking for

• 10+ years of professional software development experience or equivalent domain expertise in service-oriented architecture and large-scale distributed systems.
• Track record of serving as a technical lead with the ability to provide direction, lead multi-team initiatives, and mentor others.
• Experience building and operating production ML platforms for model training, serving, orchestration, or data systems with focus on performance and scalability.
• Strong product instincts and deep understanding of business context.
• Strong communication skills to explain complex technical concepts to both technical and non-technical stakeholders.
• Demonstrated ability to work cross-functionally with engineers, data scientists, product managers, and business stakeholders.
• Ability to operate autonomously in ambiguous environments.
• Hands-on experience using AI tools to accelerate workflow.
• Experience building large-scale ML training, serving, or data infrastructure (preferred).
• Experience with distributed ML training systems, accelerator-backed compute, and training data pipelines (preferred).
• Experience rapidly developing prototypes and iterating based on user feedback (preferred).
• Experience training and shipping machine learning models to production for business problems (preferred).
• Familiarity with LLMs, LLM application frameworks, and agentic AI patterns (preferred).
• Familiarity with cloud services like AWS and cloud-based AI/ML services (preferred).
• Ability to synthesize ideas across the organization while setting a compelling technical vision (preferred).
• Comfort working with geographically distributed teams (preferred).
• Passion for side projects, open source, or self-driven technical initiatives (preferred).