Senior Machine Learning Engineer, Supply & Competitive Intelligence

Airbnb

Senior Machine Learning Engineer developing AI and data products leveraging Airbnb’s massive datasets. Building competitive intelligence systems for understanding the global travel market.

Posted 6/3/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $196,000 - $227,000 per yearWebsite

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningPythonScalaJavafeature engineeringmodel selectionA/B testinggradient boosted treesneural networkstransformers

Soft Skills

collaborationproblem formulationcommunicationleadershipinnovationdisciplined approachorganizational skillsdata-driven decision making

Tools & Technologies

TensorFlowPyTorchCI/CDAPIsdata infrastructureML pipelinescrawling infrastructure

Certifications & Qualifications

Bachelor’s in Computer ScienceMaster’s in Machine LearningPhD in related field

Industry Keywords

competitive intelligencedata fidelityschema driftoffline trainingonline servinghigh-scale software applicationsreal-time systems

Tech Stack

Tools & technologies

JavaPythonPyTorchScalaTensorflow

About the role

Key responsibilities & impact

Design and deploy ML models that extract and structure competitive intelligence signals — supply availability, pricing patterns, and market saturation — from large-scale crawled datasets across global competitors
Build and maintain end-to-end ML pipelines spanning feature engineering, offline training, and low-latency online serving, ensuring high data fidelity and resilience to upstream schema drift
Apply entity resolution and matching techniques to accurately map competitor listings and markets to Airbnb's internal supply taxonomy, using methods such as embedding models, gradient boosted trees, and transformer-based architectures
Partner with the crawling infrastructure engineer, data engineers, and product teams to translate competitive intelligence needs into well-defined ML problem formulations and measurable success criteria
Run rigorous offline and online experiments to evaluate model quality, and collaborate with Pricing, Supply Growth, and Strategy stakeholders to turn model outputs into actionable business decisions
Stay current with the latest advances in ML and AI, identifying opportunities to incorporate new techniques into the competitive intelligence platform

Requirements

What you’ll need

5–10 years of professional experience in applied Machine Learning, with a proven track record of architecting and deploying high-impact models into production at global scale.
Exceptional programming proficiency in Python (required), with additional experience in Scala, Java, or similar languages for building robust backend systems.
Deep mastery of ML fundamentals and best practices—including feature engineering, model selection, A/B testing, and training/serving skew mitigation—alongside advanced algorithms like gradient boosted trees, neural networks, and transformers.
Hands-on expertise with modern ML frameworks and tooling, such as TensorFlow or PyTorch, to drive innovation in model development.
Experience leading data engineering efforts to build end-to-end ML pipelines, encompassing both high-throughput batch processes and low-latency real-time systems.
Strong command of architectural patterns for high-scale software applications, including the design of extensible APIs, efficient algorithms, and resilient data infrastructure.
A disciplined approach to software craft, including test-driven development, incremental delivery, and modern CI/CD deployment practices.
A Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, or a closely related technical field.

Benefits

Comp & perks

This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.