Founding ML Engineer

Role Overview

Client is hiring its first Machine Learning Engineer to bring its legal AI systems into production. This senior-level role is ideal for an experienced ML professional who can architect agentic LLM systems, develop scalable evaluation frameworks, and own full-cycle model deployment. You'll work closely with the founders and play a foundational role in defining the company s AI infrastructure.

Key Responsibilities

• Design, build, and deploy LLM-powered pipelines using tools like OpenAI, Anthropic, and Gemini

• Develop agentic AI solutions for document redlining, legal drafting, and question answering

• Collaborate with legal subject matter experts to refine prompts, evaluation metrics, and feedback loops

• Optimize inference workflows for latency, cost-efficiency, and reliability on Google Cloud Platform

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

• Mentor and guide future ML team members as the team scales

Required Qualifications

• 4 5 years of hands-on experience in ML/AI engineering, including deploying LLM systems to production

• Track record of delivering agentic or multi-agent systems, including tool-using agents

• Deep expertise in prompt engineering, including chain-of-thought and few-shot methodologies

• Strong Python engineering skills and experience with cloud deployment (Google Cloud Platform preferred)

• Ability to work cross-functionally with non-technical stakeholders and turn requirements into ML workflows

• A startup-ready mindset with ownership mentality and adaptability

Preferred Qualifications

• Background in legal-tech or other regulated industries

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

• Experience with information retrieval or fine-tuning NLP models

• Software engineering background with a transition into ML (SWE MLE)