Founding ML Engineer

Location: Strongly Preferred New York City (4 days/week)
Position Type: Full-Time (Permanent)
Work Policy: Remote, Hybrid, or In-Office (U.S. only)
Start Timeline: ASAP

Work location & travel expectations

Preferred Office: NYC (4 days/week)

Alternate: SF with 1 week/month NYC travel

Remote: U.S. only; must travel to NYC 2 weeks/month during initial ramp-up phase

Compensation

Base Salary: $0 $200,000 (dependent on interview performance, level, and location)

Equity: Competitive

About
A legal AI startup reinventing how in-house legal teams operate by automating slow and repetitive workflows.

• Founded: 2025

• Stage: Seed (Raised $3M)

• Traction: Already has customers and ~10 design partners

• Backed by: Sequoia

• Platform: Legal intake and automation hub supporting redlining, drafting, and Q&A via customizable AI agents

• Public Launch: Planned for Fall 2025

Role summary
Hiring the first ML engineer to productionize legal AI workflows. This is a senior-level role focused on architecting agentic systems using LLMs, building scalable evaluation frameworks, and owning end-to-end deployment. Youll collaborate directly with founders, take full ownership of ML systems, and play a foundational role in shaping the AI stack.

Why join

• Join a Sequoia-backed AI startup from the ground floor

• Define core ML architecture and ship agentic legal AI products

• Grow into Head of AI or CTO as company scales

• High-impact technical role with leadership trajectory

• Relocation support up to $10K for the right candidate

Tech environment

• Core Stack: Node, React, GCP, Postgres

• ML Tools: Python, OpenAI, LangChain (or equivalent), cloud ML

Responsibilities

• Architect and deploy LLM-based pipelines using OpenAI, Anthropic, Gemini, etc.

• Build agentic solutions for document redlining, Q&A, and legal drafting

• Collaborate with legal SMEs to refine prompt strategies, evaluation metrics, and feedback loops

• Optimize inference for latency, cost, and reliability on GCP

• Implement data annotation, model monitoring, and CI/CD for ML

• Mentor future ML hires as team scales

Must-have qualifications

• 4-5 years ML/AI engineering experience, including production LLM work

• Proven examples of shipped agentic solutions (e.g., multi-agent systems, tool-enabled agents)

• Hands-on expertise with prompt engineering, chain-of-thought, and few-shot techniques

• Strong Python engineering skills and experience deploying to cloud (preferably GCP)

• Ability to work with non-technical stakeholders and translate needs into ML pipelines

• Ownership mentality and ability to thrive in a startup environment

Preferred qualifications

• Experience in legal-tech or other regulated industries

• Familiarity with LLM evaluation platforms and A/B testing methodologies

• Background in NLP fine-tuning or information retrieval

• Transitioned from SWE MLE

Must NOT have

• Experience limited to research-only ML roles

• Career background exclusively at non-tech or legacy companies (e.g., banks, healthcare, Cisco, Oracle, etc.)

Interview process

• Founder Intro Call (30m): Informal chat or coffee (Zoom or in-person)

• Technical Interview (60m):

• 30m design/architecture discussion

• 30m coding assessment (candidate choice of language + IDE)

• Half-Day Onsite: Details TBD