Machine Learning Engineer, Stripe Assistant

stripe· 545 open roles

Remote RemoteFull-time2 weeks ago

Salaryest.

$150,000 - $250,000

Experience

Mid

Job Type

Full-time

Posted

2 weeks ago

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About This RoleAI processing…

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Stripe Assistant team is transforming how users interact with

Key Responsibilities

1
Establish trustworthy, human-in-the-loop execution for high-trust “write” actions—prioritizing user control, transparency, accountability, and auditability so customers can delegate with confidence.
2
Define and evolve the Assistant’s capability and governance model across hundreds of tools and agents, balancing power, permissions, and consistency at scale.
3
Raise answer quality and usefulness by grounding in authoritative Stripe knowledge and live user data, building cross-surface memory and personalization, and making the Assistant proactive and present in the dashboard.
4
Explore and apply optimal machine learning methods to improve Stripe Assistant’s overall performance, including but not limited to fine-tuning LLMs with RLHF, synthetic data generation, optimizing RAG pipelines via domain‑specific embedding and retriever fine‑tuning, and automatic prompt tuning, etc.
5
Make quality and reliability a product: set and meet SLOs, build rigorous evaluation and benchmarking loops, and drive sustained improvements in latency, cost, and availability.
6
Lead as a tech lead: mentor and grow engineers, uphold high bars for code quality, security, observability, and operational rigor, and align cross‑functionally to ship safely and fast.

Requirements

5+ years in AI/ML and backend engineering.
Applied LLM experience: RAG/embeddings, tool use/function calling, agentic planning/orchestration, fine-tuning, code generation, evaluations, etc.
Proficient in Python (Ruby is a plus); strong distributed systems fundamentals.
Experience working closely with product management, design, other engineers, and other cross-functional partners.
Experience operating ML systems at global scale with stringent SLOs—balancing reliability, latency, and cost—with privacy, security, and compliance by design.
Experience building products where AI/ML is core; as well as balancing short-term product priorities with long-term AI/ML improvements.
Track record building ML platforms, especially those that enable multiple teams to collaborate together.
Strong technical leadership and communication: mentoring and elevating engineers, elevating AI/ML awareness and posture within organizations, setting architectural direction, and driving alignment in ambiguity.