Gather is reinventing how remote teams collaborate by building immersive virtual offices that bring the energy, serendipity, and culture of in-person work into the digital world. Our platform blends the best of office life—presence, spontaneity, connection—with the flexibility and scale of remote work.

Backed by $77M in funding from top investors including Sequoia, Y Combinator, and Index Ventures, Gather is a close-knit team of 50 people on a mission to reimagine how we work in the age of distributed teams.

About the Role

The AI Experiments Team at Gather is a new innovation lab focused on transforming how AI augments knowledge work in virtual environments. As our Founding ML Engineer, you’ll be among the first hires on this team and have the opportunity to shape our strategy, test bold ideas, and build tools that redefine how teams work together.

You’ll lead the charge on fine-tuning large language models using our unique, high-signal internal data—spanning communication, collaboration, and workflows across thousands of real teams. This is a deeply hands-on role for someone passionate about debugging model behavior, shipping prototypes quickly, and turning cutting-edge ML research into production tools.

What You’ll Do

• Lead the design and implementation of fine-tuning strategies on proprietary datasets to improve model understanding of real-world work
• Rapidly build and ship internal AI tools that directly boost Gather team productivity (e.g., code helpers, knowledge bots, AI copilots)
• Collaborate with product and engineering teams to define our AI roadmap—prioritizing experiments with high business impact
• Share learnings through demos, internal docs, and potentially open source or publications
• Help build a culture of technical excellence, innovation, and curiosity within the AI team

Some Recent Experiments

• gGPT: Our internal ChatGPT powered by RAG over Notion docs and codebase
• Context Windows: Cross-platform scoped memory for each engineer across Slack, GitHub, IDE, and browser
• AI Coworker Bot: Slack bot that answers internal engineering questions
• “Write a test for this file” Plugin: VSCode extension powered by fine-tuned LLMs

Ideal Candidate

Experience & Background

• 2–5 years of experience fine-tuning LLMs or working on large model behavior in a startup or production setting
• Worked at a venture-backed startup (<100 people) or contributed significantly to open-source ML tools
• Holds a CS degree from a top-tier university (e.g., UW, Berkeley, CMU, etc.)

Technical Skills

• Strong experience with Python and model fine-tuning frameworks (e.g., TRL, LoRA/QLoRA, Axolotl)
• Familiarity with TypeScript, Node.js, and React
• Comfort debugging model performance and training issues at scale

Mindset

• Startup-ready: thrives in ambiguity and independently drives projects from idea to launch
• Intrinsically motivated: cares about solving meaningful problems over chasing hype
• Passion for AI, productivity tooling, and creating the future of work

Bonus

• Published work or open-source contributions related to LLMs or fine-tuning

Compensation & Benefits

• Salary: $180K–$250K
• Equity: Competitive RSU package
• Location: Remote (US & Canada)
• Visa: TN sponsorship or transfer available
• Team Size: <50, you’ll have a huge impact