Senior Software Engineer, ML Infrastructure

Summary

Join Airbnb and help build a suite of tools forming the foundation for ML & AI development. Contribute to a scalable platform accelerating ML design, development, and deployment of impactful ML use cases. Build scalable GenAI infrastructure supporting evolving needs using foundational language/vision models. Drive expansion of the ML platform to improve the productivity of 200+ ML engineers and data scientists. Create data foundations for data-driven product features by building scalable human & AI labeling infrastructure. Work with customer teams to deliver high-impact product wins. This US-remote eligible position requires 5+ years of industry experience, a solid understanding of engineering and infrastructure best practices, strong coding skills in Python/Java, and strong experience with distributed systems. Bonus, equity, benefits, and Employee Travel Credits may be available.

Requirements

• 5+ 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

Responsibilities

• 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

Preferred Qualifications

• Industry experience building end-to-end Machine Learning Platforms
• Experience developing and productionizing machine learning models
• Experience with Kubernetes, Spark, Docker, Airflow

Benefits

• Bonus
• Equity
• Benefits
• Employee Travel Credits