Related skills
python rag tooling llm rlhf📋 Description
- Own end-to-end ML/agent architecture for Stripe Assistant.
- Define strategy for high-trust actions; ground responses in data across Stripe and the web.
- Drive conversation continuity and personalization; deepen dashboard presence.
- Establish rigorous evaluation and SLOs; improve quality, latency, cost, and availability.
- Establish human-in-the-loop governance for high-trust actions and auditability.
- Lead as a tech lead; mentor engineers; uphold code quality, security, and operational rigor.
🎯 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.
- Proficient in Python (Ruby is a plus); strong distributed systems fundamentals.
- Experience working closely with product management, design, other engineers, and 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.
- Track record building ML platforms, especially those that enable multiple teams to collaborate together.
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