Staff Software Engineer, Machine Learning Platform

1 hour, 15 minutes ago
Full-time
Lead
Software Development
Stripe

Stripe

Stripe is a global technology company that provides financial infrastructure for the internet. They offer a suite of APIs and tools for businesses to accept online and in-person payments, automate financial processes, and embed financial services in th...

Diversified Financial Services
5K-10K
Founded 2009
$8700M raised

Description

  • Own end-to-end architecture and system design for large, complex ML Platform projects.
  • Define technical direction for ambiguous projects and translate user needs into long-term platform strategy.
  • Design solutions for challenging ML infrastructure problems, including low-latency inference, feature stores, real-time monitoring, and LLM or agent orchestration.
  • Turn high-leverage ideas into robust platform capabilities that influence product and platform roadmaps.
  • Scope and lead large business-impacting projects from requirements through design, implementation, and production operation.
  • Partner with ML engineers, data scientists, and product teams to convert needs into functional requirements and scalable technical solutions.
  • Make tradeoff decisions that balance latency, reliability, cost, and security constraints.
  • Represent engineering in discussions with senior leadership and advise on end-to-end ML lifecycle decisions.
  • Drive cross-team initiatives that improve ML development velocity and MLOps maturity.
  • Mentor and develop other engineers while modeling strong software design, implementation, and operations practices.

Requirements

  • 10+ years of professional software development experience, or equivalent domain expertise, with experience in service-oriented architecture and large-scale distributed systems.
  • Proven experience as a technical lead who can provide technical direction, lead multi-team initiatives, and mentor others.
  • Experience working on production ML platform services.
  • Strong product instincts and understanding of business context.
  • Strong communication skills with the ability to explain complex technical concepts to technical and non-technical stakeholders.
  • Demonstrated ability to collaborate cross-functionally with ML engineers, data scientists, software engineers, product managers, and business stakeholders.
  • Comfort operating with high autonomy and responsibility in ambiguous environments.
  • Hands-on experience using AI tools to accelerate work.
  • Experience building large-scale serving or data infrastructure for ML use cases, such as model inference, feature stores, real-time feature computation, or model registries (preferred).
  • Familiarity with LLMs, LLM frameworks, and agentic AI patterns such as tool use, multi-agent orchestration, or retrieval-augmented generation (preferred).
  • Experience rapidly developing prototypes and iterating based on user feedback (preferred).
  • Familiarity with cloud services such as AWS and cloud-based AI/ML services such as SageMaker, Bedrock, Databricks, or OpenAI (preferred).
  • Experience training and shipping machine learning models to production to solve critical business problems (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).

Interested in this position?

Apply directly on the company website

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