Sphere
Lead AI Engineer
San Francisco HQ
Sponsorship not specifiedDetected 288 days ago
SwiftData EngineeringLLMsRAGResearchCollaboration
About the role
- This isn't a lookup problem, it's a reasoning problem - and it only became solvable with LLMs.
- The unusual constraint: you need speed, scale, correctness, and robustness simultaneously - at millisecond latency, zero downtime, heading toward billions of transactions where a single error costs a customer $20K.
Responsibilities
- Lead development of new features aimed at increasing TRAM's test-time accuracy
- Prior experience building AI enabled products, particularly RAG systems
- You own it end to end. Give you a goal and you figure out your own path. Small team, global surface area - everyone owns a domain that would be a full team at a larger company. No one tells you how.
- You want to manage people more than own hard problems (we're a flat, experienced team - everyone builds)
Requirements
- Experience fine tuning base models, ideally via RFT
- A strong understanding of how LLMs and reasoning models function
- Experience working with LLMs on legal applications
- Experience with RAG data pipelines and collecting/curating data for the pipeline
Skills
- Own TRAM's eval framework and workflows
- Work directly with leading frontier labs to reinforce fine tune models on our proprietary data
Benefits
- Being in the room five days a week feels like a cost instead of a benefit
Company info
- Backed by a16z and YC. $21M Series A, 30%+ month-over-month growth, customers include ElevenLabs, Replit, Deel, Runway, and Lovable.
- Small team, global surface area. Everyone owns a domain that would be a full team at a larger company. San Francisco, five days in office.
- The problem keeps compounding. Expanding into input tax, withholding, e-invoicing, tariffs - each multiplies the complexity. Tens of millions of transactions today, billions ahead.
- You believe speed and accuracy are both possible. We're building a complex product that requires robustness and 100% uptime, and we have to build at our customers' pace. Move fast. Don't break things. Both.
This listing is sourced directly from Sphere's careers page and normalized into a canonical job model.