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FigmaFigmaSan Francisco, CA

Software Engineer, Machine Learning

Build and productionize ML models for search, RAG, and generative AI features at Figma. Requires 5+ years software engineering with 3+ years in applied ML, Python proficiency, and experience with scalable data pipelines.

149k – 350k/yr
Remote5+ YOEML Engineering

About the role

What you’ll do at Figma:

  • 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.

We’d love to hear from you if you have:

  • 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.

While not required, it’s an added plus if you also have:

  • 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.
  • A product mindset with the ability to tie technical work to user outcomes and business impact.
  • Strong collaboration and communication skills.

Skills

PythonPyTorchTensorFlowscikit-learnSpark MllibXgboostRAGMLOpsNLPKubernetes

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