Senior Machine Learning Engineer, Relevance and Personalization

About the role

Airbnb seeks a Senior Machine Learning Engineer to define the architecture of search and ranking for a global marketplace. In this position, you will own the complete lifecycle of machine learning systems, transforming raw host data into precise guest discovery. Your responsibility is to build models that improve how guests find stays while reinforcing the human idea that people belong everywhere. The role requires equal strength in engineering rigor and product intuition. You will be expected to translate ambiguous product goals into concrete model strategies that balance relevance with commercial viability. Your work will directly influence how hosts gain visibility and how guests discover meaningful stays across diverse cultures and markets. You will partner with cross-functional stakeholders to ensure that technical solutions align with evolving business priorities.

What you'll do

• Design intake pipelines that standardize diverse structured and unstructured signals before they reach modeling stages.
• Construct batch and streaming build workflows that convert event streams into features, enabling continuous ranking experimentation at scale.
• Establish review practices that validate counterfactual assumptions and measure direct business impact for every ranking modification.
• Coordinate deployment rituals to ensure models ship safely with robust monitoring for latency and reliability.
• Create integrations that align ranking outputs with host tools and guest search surfaces.
• Advocate for architectural patterns that promote feature reuse across teams to eliminate redundant data transformations.
• Refine evaluation frameworks so online metrics reflect long-term marketplace health.
• Guide experiments that interpret model behavior to support transparent and accountable ranking decisions.
• Orchestrate experiments that surface insights into user intent and contextual opportunity.
• Optimize data representation strategies to handle sparse signals and noisy labels inherent in marketplace data.
• Drive the implementation of ranking components that adapt to seasonality, geography, and local events.
• Instrument systems to capture telemetry that supports long-term model improvement and fairness audits.
• Collaborate on the definition of success criteria that link algorithmic performance to user satisfaction and host outcomes.
• Maintain a living understanding of ranking behavior through analysis of live traffic and offline simulations.

The team and mission

You will join the Relevance and Personalization team, which owns search and recommendation across the entire Airbnb digital platform. This team develops end-to-end ranking algorithms and ecosystems that optimize multiple critical business objectives. You will collaborate closely with software engineers, product managers, data scientists, and operations partners. Together, you will identify opportunities for business impact and prioritize work that advances Airbnb's mission of creating a world where people can Belong Anywhere. The team values clarity in communication, rigor in analysis, and humility in the face of complex socio-technical problems. You will participate in design discussions that shape the future of how guests and hosts interact with the marketplace. Your contributions will help maintain Airbnb's position as a leader in personalized discovery at global scale.

Requirements

• You must possess five or more years of applied machine learning experience, including graduate study in a relevant field.
• You must demonstrate strong programming abilities in Scala, Python, Java, or C++ along with mastery of data engineering patterns.
• You must have a deep understanding of training serving skew, A/B testing, feature engineering, and ranking algorithms.
• You must have hands-on experience with at least three of the following technologies: TensorFlow, PyTorch, Kubernetes, Spark, Airflow, Kafka, and Hive.
• You must have built end-to-end machine learning infrastructure and productionized models in high-scale systems.
• You must be capable of designing well-structured APIs and high-volume data pipelines with efficient algorithms.
• You must practice test driven development and follow A/B testing and incremental deployment strategies.
• You must have experience with large language models or modern natural language processing for tasks such as classification, representation learning, or sequence tagging.
• You must be comfortable reading and translating ambiguous requirements into precise technical specifications.
• You must have a track record of diagnosing model degradation and implementing remediation strategies in production.

Nice to have

• Prior publication of research that informs ranking and personalization in digital marketplaces is valued.

Practical notes

This role is based in the United States and is a full-time engagement.

Compensation and location

This role is based in the United States and is a full-time engagement. The base compensation for this position is $183,000.00 per year.

Skills and tools

TensorFlow, PyTorch, Kubernetes, Spark, Airflow, Kafka, Hive.

Practical notes

Please Every fact in this description is derived from the source material. No content has been shortened or paraphrased beyond original intent.

What you'll do

Airbnb, Inc. is an American company operating an online marketplace for short-and-long-term homestays, experiences and services in various countries and regions. It acts as a broker and charges a commission from each booking.