> Markdown version of [/jobs/ext/4624544-staff-software-engineer-ai-platform](https://www.wearedevelopers.com/jobs/ext/4624544-staff-software-engineer-ai-platform). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Software Engineer AI, Platform - **Company:** Airbnb - **Location:** Chicago, IL, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, Distributed Systems, Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Pytorch, LangChain, Apache Spark, Kubernetes, Machine Learning Operations, Software Coding, Docker - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25303_10ab0e80d9f03a7de26a32b919680139 ## About the Role * 9+ years of industry experience (and/or relevant academic experience) * Solid understanding of engineering and infrastructure best practices * Strong coding skills in Python/Java or equivalent * Strong Experience and knowledge of distributed systems * Industry experience building end-to-end Machine Learning Platforms is a plus * Experience developing and productionizing machine learning models is a plus * Experience with Kubernetes, Spark, Docker, Airflow is a plus ## Description * Build scalable GenAI infrastructure to support the fast evolving needs of Airbnb teams using foundational language / vision models to power next-gen product experiences * Drive expansions of our ML platform to improve the productivity of 200+ ML Engineers & Data Scientists who rely on us * Create solid data foundations to power the data-driven product features (e.g. Categories) that are at the center of Airbnb's product roadmap by creating scalable human & AI Labeling infrastructure * Use OSS technologies such as Ray, MLFlow, Tensorflow, PyTorch, LangChain, Airflow, Spark, Docker, Kubernetes, Jupyterhub, etc. * Work side-by-side with customer teams including Customer Support, Search Relevance, Trust & Safety to deliver high-impact product wins