Research Engineer

Ando • San Francisco, CA

9d

About The Position

We’re looking for a Founding Research Engineer to drive our applied AI efforts from the ground floor. You’ll take the lead on shaping how we use language models, retrieval, and evaluation to make agents genuinely useful in a fast-paced, enterprise context. Ando Teams are already building AI agents and plugging them into Slack, email, and other tools. But those platforms weren’t designed for human–AI collaboration. We’re not making “a slightly better Slack.” We’re re-architecting workplace communication from the ground up so humans and agents can actually work together.

Requirements

• Experience in applied NLP / IR / ML research (LLMs, semantic search, QA, embeddings, knowledge graphs, etc.)
• Comfort working across the stack - from modeling and data to infrastructure and evaluation
• Strong sense for product - able to judge not just what’s technically possible, but what makes for an amazing user experience
• A “negative maintenance” mindset: self-driven, detail-oriented, poised under pressure, and constantly improving

Nice To Haves

• You like the messy beauty of early stage, and you want the late nights with a small team that you’ll remember years later
• You prefer the dopamine of working on software that will get into hundreds of thousands of users' hands, vs working on enterprise, forward-deployed software
• You want to do the best work of your life with people who push you to be better, and you want to help build that team too
• You don't love LLMs / don't use them daily - And if you're not there yet, you should endeavor to be a DAU!
• You don't value craft and cannot speak to software that inspires you

Responsibilities

• Own our message tagging system; iterate on it and continually expand the parameters and methods with which we create meta-context around Ando workspaces
• Develop a state of the art retrieval system for knowledge search and in-context reasoning
• Lead research in query understanding, spanning semantic search, question answering, summarization, and knowledge graph integration
• Architect and scale ML infrastructure and evaluation pipelines
• Collaborate closely with product and design to define what is possible on the UI-side, and also to observe users and translate messy, human workflows into crisp technical systems
• Stay close to cutting-edge research (e.g. you should have read Cartridges, MemGPT, etc) but ship production-ready features that feel magical to users

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed