Research Engineer

We're building the creative layer for modern communication. Every month, over a billion people make presentations — but the tools they use to make them haven't evolved in decades. We're changing that, using AI to disrupt a massive market.

📈 Millions of people rely on Gamma to create, teach, and persuade, creating more than 1 million gammas every day.

💻 We see Gamma as the next great workplace tool, combining viral B2C love with a massive B2B opportunity. We believe AI can be a true creative partner: one that understands context, clarity, and taste.

💸 We’ve reached a $2.1B valuation
, crossed $100M in annual recurring revenue
, and have been profitable since 2023.

💙 We're an imaginative, passionate team who takes our work seriously, but not ourselves. Our culture is warm, a little quirky, and fueled by curiosity.

You'll own the quality of AI across everything Gamma creates. As our Research Engineer, you'll design evaluation frameworks that measure AI output quality, systematically improve production prompts, and fine‑tune models to ensure millions of users get exceptional results every time they generate content with Gamma.

This role sits at the intersection of research rigor and product impact. You'll diagnose failure patterns in AI‑generated presentations, docs, and websites, then craft targeted improvements through iterative experimentation. You'll build the tools and workflows that enable rapid testing, validate changes against quality benchmarks, and ensure our AI gets smarter with every iteration. If you're obsessed with output quality and love the challenge of making AI systems work beautifully at scale, this is your role.

You'll succeed here if you combine deep technical expertise with a research‑oriented mindset. You need to be comfortable working in ambiguity, designing experiments that reveal model behavior, and iterating toward solutions that measurably improve quality. Exceptional attention to detail is essential, as is the ability to care about dimensions of quality that others might overlook.

Our team has a strong in‑office culture and works in person 4–5 days per week in San Francisco. We love working together to stay creative and connected, with flexibility to work from home when focus matters most.

Design and maintain evaluation frameworks that measure AI output quality across all Gamma experiences, developing metrics and benchmarks to assess model performance.

Systematically improve production prompts through iterative experimentation—diagnosing failure patterns, crafting targeted improvements, and validating against quality benchmarks.

Conduct rigorous experiments to understand model behavior, analyze results, and derive insights that inform prompt and model improvements.

Build tools and workflows to support rapid experimentation and quality analysis, enabling faster iteration on AI improvements.

Fine‑tune models on targeted datasets to improve baseline performance, preventing issues like poor layout choices or low‑quality outlines.

Partner with product and engineering teams to ensure AI quality improvements ship quickly and work reliably at scale.

1–2+ years working with AI systems with demonstrated experience shipping production‑grade AI products.

Deep hands‑on experience with prompt engineering, LLM experimentation, and systematic evaluation of AI outputs.

Strong experimental mindset with ability to design tests, analyze model performance, and iterate toward quality improvements.

Experience with post‑training techniques for LLMs including reinforcement learning and supervised fine‑tuning.

Research‑oriented approach to problem‑solving with comfort working in ambiguity and exploring novel solutions to AI quality challenges.

Exceptional attention to detail and quality obsession—cares deeply about output quality across all dimensions, including less visible aspects.

Bachelor's degree in Computer Science, Machine Learning, or related field, or equivalent hands‑on experience with AI research and experimentation (Nice to have).

Final offer amounts are determined by multiple factors, including but not limited to experience and expertise…