Senior Machine Learning Engineer, Supply & Competitive Intelligence

About Airbnb: Airbnb is a premier, internationally recognized hospitality platform pioneer, global marketplace innovator, and data-driven technology leader on an absolute mission to empower authentic community connections worldwide. Born in 2007 from a single home hosting experience, Airbnb has expanded exponentially to encompass over 5 million hosts who have welcomed more than 2 billion guest arrivals across almost every country and territory on earth. Operating via highly distributed cloud topologies and advanced artificial intelligence layers, Airbnb unifies millions of global listing variations, complex regional pricing dynamics, and real-time demand patterns into a seamless consumer ecosystem. Airbnb champions an inclusive, creatively led workspace where engineering excellence, diversity of thought, and structural ownership are continuously leveraged to redefine the global travel industry.

Position Overview

We are seeking a highly sophisticated, mathematically minded Senior Machine Learning Engineer, Supply & Competitive Intelligence to join our core Marketplaces Data and AI cell within the global Guest and Host organization. This position is open in a full-time remote-eligible capacity for qualified machine learning specialists permanently residing within registered entity states in the United States. In this highly critical data engineering seat, you will claim individual accountability for leading the architectural design and deployment of the machine learning engines backing our enterprise Competitive Intelligence infrastructure. Moving entirely away from standard boilerplate modeling setups, you will build the production systems that process massive scraped datasets to give Airbnb a real-time, comprehensive understanding of the global travel market’s pricing models, listing structures, and supply saturation thresholds. This high-agency role demands a seasoned applied scientist who writes robust code, commands profound pipeline logic, and can effortlessly bridge technical model predictions with long-term macroeconomic business strategies.

Key Responsibilities

• Intelligence Signal Extraction: Design, optimize, and deploy state-of-the-art machine learning models to extract and structure hidden competitive intelligence signals—including hyper-localized supply availability and pricing behaviors—from global competitor networks.
• End-to-End Pipeline Engineering: Build, audit, and maintain resilient end-to-end machine learning pipelines, cleanly structuring advanced feature engineering pipelines, high-throughput offline training batches, and low-latency online serving engines.
• Entity Resolution & Listing Mapping: Apply sophisticated entity resolution, de-duplication, and semantic matching techniques to map complex competitor datasets into Airbnb’s unified internal supply taxonomy.
• Advanced AI Architecture Selection: Implement, tune, and evaluate advanced algorithmic structures, natively choosing between gradient boosted trees, custom deep neural networks, and transformer-based architectures to process web-scale datasets.
• Cross-Functional Problem Formulation: Partner closely with scraping infrastructure engineers, cloud data developers, and product managers to translate complex competitive business criteria into tractable machine learning problem statements.
• Rigorous Statistical Experimentation: Run comprehensive offline validation tests and live online A/B testing variations to accurately measure predictive model quality and guarantee high data fidelity against upstream schema changes.
• Upstream Schema Drift Mitigation: Engineer robust pipeline defensive guardrails to systematically address and isolate training-serving data skew, preserving core execution stability across distributed backend microservices.
• Continuous Technological Research: Monitor and track the latest advancements across the broader open-source AI community, incorporating next-generation TensorFlow or PyTorch primitives to scale system-level capabilities.

Required Skills & Qualifications

• 5–10 years of verified professional history running applied Machine Learning, predictive data science engineering, statistical signal extraction, or full-scale data pipeline construction.
• Proven real-world track record of architecting, deploying, and monitoring high-impact, high-concurrency machine learning models inside live production environments at global scale.
• Expert-tier programming literacy and demonstrable development depth in the Python language, paired with exposure to backend platforms using Scala or Java.
• Deep theoretical and practical mastery of core machine learning primitives, encompassing feature engineering methodologies, complex model selection, A/B testing design, and data skew mitigation.
• Hands-on production proficiency writing and configuring neural architectures natively utilizing advanced frameworks like TensorFlow or PyTorch.
• Strong command of architectural design patterns for high-scale software services, including building extensible web APIs, efficient data matching algorithms, and resilient storage layouts.
• A disciplined approach to the software craft, highlighting a clear adherence to test-driven development (TDD), incremental component delivery, and modern CI/CD automation practices.
• A Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, Data Engineering, Applied Mathematics, or a closely related quantitative field.
• Location Context: Parameters open to qualified technical leads permanently based anywhere within the United States (restricted to states where Airbnb has an active registered entity for remote employment).

Preferred Strategic Indicators (Nice to Have)

• Prior experience designing competitive analytics tools, algorithmic dynamic pricing engines, or high-throughput web scraping parsers for a high-velocity internet consumer brand.
• Familiarity with distributed data processing environments, such as orchestrating high-volume analytics jobs within Apache Spark or Hadoop networks.
• Exposure to deep learning embedding models, visual feature matching, or multi-lingual natural language processing (NLP) pipelines.

What We Offer

• The exceptional professional canvas to directly direct, code-shape, and deploy the machine learning architectures driving real-time competitive strategies for the world’s largest travel marketplace.
• Highly competitive baseline salary structures calibrated transparently between $196,000 – $227,000 USD per year, inclusive of career level matching and market demand evaluations.
• Profound work-from-home remote parameters offering high lifestyle flexibility, complete execution trust, and occasional fully supported corporate offsite attendance.
• Immediate eligibility to access lucrative corporate bonus opportunities, meaningful company equity allocations, and comprehensive healthcare protection coverages.
• Generous inclusive benefits programs, retirement savings plan integrations, and specialized corporate Employee Travel Credits to explore global Airbnb destinations firsthand.