Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
API
LLM
Machine Learning @ 6
RAG
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Stripe is a financial infrastructure platform for businesses. The Conversation Platform team is building a platform for Stripe merchants by automating easy tasks and assisting users with difficult tasks. Examples include customizing Stripe landing pages to suggest bespoke integrations, enabling users to command the Stripe API in natural language, and automatically resolving user issues.
The team develops retrieval-augmented generation (RAG) systems using the latest large language models (LLMs), fine-tunes its own models, and works end to end from ideation and modeling through production deployment.
Responsibilities
- Drive an ambitious AI and machine learning vision that benefits users.
- Set the technical and process direction for the team based on business goals.
- Brainstorm and coordinate product integrations with partner teams.
- Propose new ideas and build prototypes.
- Contribute to the broader internal and external machine learning community.
- Hire and develop a world-class team to deliver high-quality machine learning systems.
- Coach engineers to support their career growth and maintain a high technical bar.
Requirements
- At least 4 years of experience managing machine learning teams.
- Experience working as a Machine Learning Engineer, Applied Scientist, or equivalent individual contributor.
- Ability to lead by example in high-growth, high-impact, ambiguous environments.
- Experience building and shipping machine learning systems.
- High standards for production systems and engineering quality.
- Ability to thrive in a collaborative, cross-functional environment.
Preferred Qualifications
- Experience shipping large language model and retrieval-augmented generation systems.
Technologies and Systems
- Machine learning models
- Streaming feature pipelines
- Large language models (LLMs)
- Retrieval-augmented generation (RAG)
- Stripe API integrations
- Backend systems
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