Staff Machine Learning Engineer, Relevance Research

Airbnb was born in 2007 when two Hosts welcomed three guests to their San Francisco home, and has since grown to over 4 million Hosts who have welcomed more than 1 billion guest arrivals in almost every country across the globe. Every day, Hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.

The Community You Will Join:

The Airbnb Relevance is Airbnb’s personalization and intelligence platform that provides support to our Community of millions of guests and hosts who take trips and join experiences around the world every year. With a deep understanding of guests, Hosts, Trips, and the Airbnb ecosystem, Relevance builds ranking and recommendations (I’m Flexible Category ranking, Split Stays, Search Ranking for Stays and Experiences, Autocomplete, Recommendations on P2, PDP Highlights, and many others surfaces) to enable magical trips at scale. 

Within Relevance, the Intelligent Platform team is responsible for the key  product and technology pillar that enables intelligent, scalable and exceptional AI/ML service experiences across Airbnb.

The Difference You Will Make:

As a senior technical individual contributor, you will bring a unique skill set and experience to our organization, lead the architecture and design of the Relevance Intelligence Platform product, and work to solve some of the broader technical challenges within the organization. You will work both on the overall Relevance Intelligence Platform architecture and future vision for the business, but will also lend expertise to specific teams and deep dive into projects as needed.

Our engineering organization is one where we value everyone’s input and ideas. Although you will be at the Principal level, all individual contributors at Airbnb are Software Engineers, will be expected to be hands on, and contribute code.

A Typical Day: 

• Define overall technical architecture for major parts of the Relevance Intelligent Platform and Product
• Architect large scale reliable Advanced AI/ML Based systems to support continuous growth of the business
• Influence the organization, engineering leaders, product managers, and the business to develop a unified approach to Intelligence Platforms at Airbnb
• Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases.
• Understand how key technical decisions will drive business outcomes.
• Perform design and code reviews and advice/mentor other AI/ML engineers at Airbnb.
• Champion the best AI/ML engineering practices and build the engineering excellence culture in the organization.
• Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact.
• Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
• Leverage third-party and in-house Machine Learning tools & infrastructure to develop reusable, highly differentiating and high-performing Machine Learning systems, enable fast model development, low-latency serving and ease of model quality upkeep.
• Example projects include: feature platform, model interpretability, hyperparameter optimization, concept drift detection.

Your Expertise:

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• 15 years of technical experience in Applied Machine Learning inclusive MS or PhD in relevant fields, including producing code for a production system and shipping production systems.
• Strong programming (Scala / Python / Java/ C++ or equivalent), data engineering skills and experience with 3 or more of these technologies: Tensorflow, PyTorch, Spark, Kafka
• Deep understanding of Machine Learning best practices (eg training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg natural language processing, computer vision, personalization and recommendation, anomaly detection)
• Experience with Machine Learning (AI/ML), including working with training models and developing existing model structures.
• Experience with test driven development, familiar with A/B testing, incremental delivery and deployment
  

Your Location:

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