Staff Software Engineer, Machine Learning Platform
Remote • San Francisco, Seattle
Posted 10d ago
Job Location
San Francisco, Seattle
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
Stripe is seeking a Staff Software Engineer to join the Machine Learning Platform team. This role involves technical leadership and significant contributions to the evolution of platforms powering Stripe's ML-driven products. You will influence investments and strategy, enhance system reliability, security, and usability, and collaborate cross-functionally to amplify ML's impact across the company. The team builds and maintains the platforms and services that enable ML engineers and data scientists to develop and deploy models from prototype to production at scale, covering areas like ML training, model serving, feature computation, observability, and agentic AI capabilities.
Responsibilities
- Serve as a technical lead and key contributor to ML Platform evolution.
- Make high-impact decisions influencing Stripe's ML investments and strategy.
- Enhance system reliability, security, and user experience.
- Define long-term strategy and technical direction for next-generation ML infrastructure.
- Take ownership of end-to-end architecture and system design for complex ML Platform projects.
- Define technical direction for ambiguous projects, translating user needs into platform strategy.
- Design system architectures for challenging ML Platform problems, including AI/ML workflow orchestration, scalable CPU/GPU compute, model training, LLM fine-tuning, low-latency inference, large-scale feature stores, real-time monitoring, and LLM/agent orchestration.
- Develop robust solutions that shape platform and product roadmaps.
- Scope and lead large projects with significant business impact from requirements to production.
- Translate needs from ML engineers, data scientists, and product teams into scalable technical solutions.
- Arbitrate critical decisions balancing competing priorities (latency, reliability, cost, security).
- Act as a key engineering representative, advising leadership on ML lifecycle technical considerations.
- Drive cross-team initiatives to improve ML development velocity and MLOps maturity.
- Mentor and grow other engineers, serving as a role model for system design and operation.
Requirements
- 10+ years of professional software development experience or equivalent domain expertise.
- Solid background in service-oriented architecture and large-scale distributed systems.
- Proven track record as a technical lead, providing technical direction and mentoring.
- Experience building and operating production ML platforms (e.g., model training, serving, orchestration, data systems) with performance, reliability, scalability, and cost efficiency requirements.
- Strong product instincts and understanding of business context.
- Excellent communication skills, able to explain complex technical concepts to diverse stakeholders.
- Demonstrated ability to work cross-functionally with various teams (ML engineers, data scientists, SWEs, PMs, business stakeholders).
- Ability to thrive with high autonomy and responsibility in ambiguous environments.
- Hands-on experience using AI tools to accelerate work.