AI Applied Scientist
FigmaSan Francisco, CA • New York, NY • United StatesPosted 24 February 2026
Tech Stack
Job Description
<div class="content-intro"><p>Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us!</p></div><div class="section page-centered">
<p>We’re looking for applied scientists with a Machine Learning and Artificial Intelligence background to build AI technologies and make Figma products more magical.. You will be driving fundamental and applied research in this area. You will be combining industry best practices and a first-principles approach to design and build AI/ML models and systems to improve Figma’s products.</p>
<p>This is a full time role that can be held from one of our US hubs or remotely in the United States.</p>
<h4><strong>What you’ll do at Figma:</strong></h4>
<ul>
<li>You will be driving fundamental and applied research in AI. You will explore the boundaries of what is possible with the current technology set to build best in class models for Figma’s domains</li>
<li>You will be combining industry best practices and a first-principles approach to build cutting edge Generative AI models, using techniques like Supervised Finetuning (SFT), Reinforcement Learning (RL), prompt improvements and synthetic data generation</li>
<li>Work in concert with product and infrastructure engineers to improve Figma’s products through AI powered features</li>
<li>Collaborate closely with product managers and engineers to transform user feedback into requirements for AI systems</li>
<li>Build evaluation systems to measure and improve quality of AI features in Figma products</li>
</ul>
<h4><strong>We'd love to hear from you if you have:</strong></h4>
<ul>
<li>Extensive experience in building generative AI features through prompt engineering, and fine tuning models in production environments</li>
<li>Experience working on deep learning and generative AI frameworks like PyTorch, JAX, HuggingFace etc</li>
<li>Experience training LLMs with Reinforcement Learning techniques such as preference-based RL (DPO, PPO) and/or RL with verifiable rewards (RLVR) such as GRPO/DAPO. Experience with RL from execution feedback for Coding, and RL with non-verifiable rewards will be a plus</li>
<li>4+ years in Generative AI, and 6+ years of experience in one or more of the following areas: machine learning, natural language processing/understanding, computer vision</li>
<li>Strong software engineering skills with 5+ years of experience in programming languages (Python, C++, Java or R)</li>
<li>Experience communicating and working across functions to drive solutions</li>
</ul>
<h4><strong>While not required, It’s an added plus if you also have:</strong></h4>
<ul>
<li>Proven track record of planning multi-year roadmap in which shorter-term projects ladder to the long-term vision</li>
<li>Experience in mentoring/influencing senior engineers across organizations</li>
<li>Expertise working on large scale and distributed AI training</li>
</ul>
<p>At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.</p>
</div><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p><strong><span style="font-size: 16px;">Pay Transparency Disclosure</span></strong></p>
<p>If based in Figma’s San Francisco or New York hub offices, this role has the annual base salary range stated below. </p>
<p>Job level and actual compensation ... (truncated, view full listing at source)
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