Staff Software Engineer, Data for ML

Airbnb is seeking a Staff Software Engineer to lead data initiatives within their Communication and Connectivity (CnC) organization. This role sits at the intersection of data engineering and machine learning, focusing on building scalable systems that power the company's ML models and product features.

The position involves designing and implementing both batch and real-time data processing systems, with a particular emphasis on GenAI and large language models (LLMs) to enhance the Airbnb experience, especially in high-traffic areas like Messaging. You'll be responsible for creating robust ML infrastructure and optimizing for performance, scalability, and cost-effectiveness.

As a staff engineer, you'll play a crucial role in shaping the team's long-term vision and roadmap, working closely with cross-functional partners across Airbnb. The role requires strong technical expertise in distributed data processing frameworks like Apache Spark or Flink, combined with the ability to mentor other engineers and influence the broader data engineering community at Airbnb.

The position offers a competitive compensation package ranging from $204,000 to $255,000 USD, plus benefits including equity, bonuses, and Employee Travel Credits. This is a remote-eligible position within the United States, with occasional office visits or offsites as needed.

The ideal candidate will bring 9+ years of industry experience (or 6+ with a PhD), strong CS fundamentals, and a proven track record of working on end-to-end Machine Learning products. You'll be joining a company that values diversity, inclusion, and belonging, working on products that connect millions of hosts and guests worldwide.

This role presents an exciting opportunity to work at the forefront of AI/ML technology while making a significant impact on how people connect and experience travel through Airbnb's platform. You'll be part of a team that's pushing the boundaries of what's possible in communication and connectivity, while helping to scale Airbnb's data infrastructure for the future.