Key skills
Machine LearningPythonML model developmentData pipelinesAI infrastructureCollaboration skillsCommunication skillsMentoringC++CGoAIMLNLPGenerative AIPyTorchTensorFlowscikit-learnMLOpsXGBoostSparkCI/CDFigmaCommunicationCollaboration
About this role
Figma is a company on a mission to make design accessible to all, and they are seeking a versatile and experienced Machine Learning / AI Engineer to join their growing AI team. The role involves building intelligent search systems, scalable data pipelines, and enhancing AI-powered creativity tools to drive user productivity and advance AI at Figma.
Responsibilities:
- Design, build, and productionize ML models for Search, Discovery, Ranking, Retrieval-Augmented Generation (RAG), and generative AI features
- Build and maintain scalable data pipelines to collect high-quality training and evaluation datasets, including annotation systems and human-in-the-loop workflows
- Collaborate with AI researchers to iterate on datasets, evaluation metrics, and model architectures to improve quality and relevance
- Work with product engineers to define and deliver impactful AI features across Figma’s platform
- Partner with infrastructure engineers to develop and optimize systems for training, inference, monitoring, and deployment
- Explore new ideas at the edge of what’s technically possible and help shape the long-term AI vision at Figma
Requirements:
- 5+ years of industry experience in software engineering, with 3+ years focused on applied machine learning or AI
- Strong experience with end-to-end ML model development, including training, evaluation, deployment, and monitoring
- Proficiency in Python and familiarity with ML libraries like PyTorch, TensorFlow, Scikit-learn, Spark MLlib, or XGBoost
- Experience designing and building scalable data and annotation pipelines, as well as evaluation systems for AI model quality
- Experience mentoring or leading others and contributing to a culture of technical excellence and innovation
- Familiarity with search relevance, ranking, NLP, or RAG systems
- Experience with AI infrastructure and MLOps, including observability, CI/CD, and automation for ML workflows
- Experience working on creative or design-focused ML applications
- Knowledge of additional languages such as C++ or Go is a plus, but not required
- A product mindset with the ability to tie technical work to user outcomes and business impact
- Strong collaboration and communication skills, especially when working across functions (engineering, product, research)