• Build and improve inventory demand forecasting models using ML and statistical methods. • Own ML models end-to-end: data collection → feature engineering → training → deployment → monitoring → iteration. • Develop decision systems that support inventory planning, pricing, and demand decisions. • Build and maintain data pipelines and API integrations for external and internal data sources. • Work with messy real-world data to ensure model reliability through rigorous validation and testing. • Implement LLM/AI-agent workflows to translate domain logic into automated processes. • Operate independently in a small team, setting priorities, unblocking challenges, and communicating tradeoffs clearly.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As a senior technical individual contributor, you will partner closely with our leaders across the broader technical organization helping design, execute and deliver in a complex and collaborative roadmap of Trust engineering efforts that will require collaboration across many parts of the organization and many parts of Airbnb. Although you will be at one of our highest levels of seniority, all individual contributors at Airbnb are Software Engineers which means we expect you to be hands on and contribute code. - Define and execute on the long-term ML technical vision and strategy for the Trust organization, identifying key investments, architecting scalable solutions, and championing best practices that advance the state-of-the-art in production ML systems. - Serve as a technical leader and mentor to other ML and software engineers across the organization, providing guidance on complex architectural and modeling challenges, and raising the overall technical bar. - Drive and deliver large-scale, multi-quarter ML initiatives that span multiple teams, influencing roadmaps and ensuring alignment between platform and product. - 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. - 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. - Work closely with other trust defense and platform teams to tackle the changing landscape of fraud attacks. - Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases. - Examples include: Anomaly detection models, ML models for continuous risk evaluation, Multimodality and Agentic AI. Qualifications - 12+ years of industry experience in applied Machine Learning. - 2-3+ years working with LLMs and novel GenAI technologies. Proficiency and proven experience on Agentic AI (frameworks, orchestration, architecture and productionization). - A Bachelor’s, Master’s or PhD in CS/ML or related field. - Strong programming (Scala / Python / Java/ C++ or equivalent) and data engineering skills. - Deep understanding of Machine Learning best practices (e.g., training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (e.g., gradient boosted trees, neural networks/deep learning, optimization) and domains (e.g., genAI, Agentic AI, natural language processing, computer vision, personalization and recommendation, anomaly detection). - Experience with these technologies: AgenticAI, Tensorflow, PyTorch, Kubernetes. - Industry experience building end-to-end Machine Learning and Agentic infrastructure and/or building and productionizing Machine Learning models. - Exposure to architectural patterns of a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models). - Experience with test driven development, familiar with A/B testing, incremental delivery and deployment. - Experience with the Trust and Risk domain is a plus. Requirements - This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. - While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. - Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. - If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from. Benefits - Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. - The base pay range is subject to change and may be modified in the future. - This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits. - Pay Range: $244,000 — $305,000 USD.

Liftoff is a leading AI-powered performance marketing platform for the mobile app economy. Our end-to-end technology stack helps app marketers acquire and retain high-value users, while enabling publishers to maximize revenue across programmatic and direct demand. Liftoff’s solutions, including Accelerate, Direct, Monetize, Intelligence, and Vungle Exchange, support over 6,600 mobile businesses across 74 countries in sectors such as gaming, social, finance, ecommerce, and entertainment. Founded in 2012 and headquartered in Redwood City, CA, Liftoff has a diverse, global presence. About the Revenue Engine team The Revenue Engine team works to understand the fundamental economics of the mobile ad tech marketplace, including the elasticity of demand and the effects of competition. The team of machine learning engineers, software engineers, and data analysts develops theories, validates those theories with experiments and analyses, and uses the learnings to build production systems that improve outcomes for Liftoff and its advertisers. As a Machine Learning Engineer on the Revenue Engine team, you will: - Build statistical models and production systems to balance advertiser performance with business goals. - Tune optimization parameters, measure internal competition, and model dynamic environments. - Design and run experiments to validate theories underpinning the mobile ad tech economy. - Develop applications in the areas of advertiser budget retention and growth, optimal margin allocation, and bidding innovations. - Collaborate with a team of world-class engineers with diverse backgrounds as well as peers across the broader company (e.g. Operations, GTM). - Use strong communication skills (verbal and written) to explain statistical and machine learning concepts to both technical and non-technical audiences. - Be part of an “engineering excellence” culture through state-of-the-art tools, risk-driven testing, explainable systems, and design/code review. Requirements: - PhD in Computer Science, Machine Learning, Economics, or a related field. - Industry experience applying economics or machine learning to large scale problems. - Solid engineering and coding skills. - Excellent team communication and collaboration skills. - Experience with ad tech is a solid plus. Location: This role is eligible for full-time remote work in one of our entities: CA, CO, ID, IL, FL, GA, MA, MI, MN, MO, NJ, NV, NY, OR, TX, UT, and WA. We are a remote-first company with US hubs in Redwood City, Los Angeles, and New York City. Travel Expectations: We offer several opportunities for in-person team gatherings, including but not limited to project meetings, regional meetups, and company-wide events. We expect our employees to attend these gatherings at least once per quarter. These gatherings provide essential opportunities for collaboration, communication, and team building. Compensation: Liftoff offers all employees a full compensation package that includes equity and health/vision/dental benefits associated with your country of residence. Base compensation will vary based on the candidate's location and experience. The following are our base salary ranges for this role: - SF Bay Area, Los Angeles/Orange County, NYC, Seattle: $235,000 - $275,000 - All other cities and towns in our approved states: $215,000 - $255,000 #LI-EL1 #LI-REMOTE We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process, we provide Covey with job requirements and candidate-submitted applications. We began using Covey Scout for Inbound on January 22, 2024. Please see the independent bias audit report covering our use of Covey here. Liftoff offers a fast-paced, collaborative, and innovative work environment where employees are empowered to grow and make an impact. We’re shaping the future of the mobile app ecosystem—join us and help accelerate what’s next. Liftoff’s compensation strategy includes competitive salaries, equity, and benefits designed to support employee well-being and performance. We benchmark compensation based on role, level, and location to ensure fairness and market alignment. Benefits may include medical coverage, wellness stipends, and additional perks based on your country of residence. Liftoff is an equal opportunity employer. We are committed to creating an inclusive environment for all employees and applicants regardless of race, ethnicity, national origin, age, marital status, disability, sexual orientation, gender identity, religion, veteran status, or any other characteristic protected by applicable law. Agency and Third Party Recruiter Notice: Liftoff does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or Recruiting Team. All candidates must be submitted via our Applicant Tracking System by approved Liftoff vendors who have been expressly requested to make a submission by our Recruiting Team for a specific job opening. No placement fees will be paid to any firm unless such a request has been made by the Liftoff Recruiting Team and such a candidate was submitted to the Liftoff Recruiting Team via our Applicant Tracking System.

• Design and Develop machine learning infrastructure, tooling, and models to help teams deliver world class experiences. • Help product and development teams understand the data lifecycle and the inherent experimental nature of machine learning. • Build internal products and platforms to enable teams to incorporate AI into their features and customer facing products. • Consult with teams to help them understand common patterns, anti-patterns, and tradeoffs of machine learning. Guide them through creating excellent customer experiences end to end. • Build scalable, resilient services to support data integration, event processing, and platform extensions. • Contribute to the continued evolution of product functionality that services large amounts of data and traffic. • Write code that is high-quality, performant, sustainable, and testable while holding yourself accountable for the quality of the code you produce. • Coach and collaborate inside and outside the team. You enjoy working closely with others - helping them grow by sharing expertise and encouraging best practices. • Work in a cloud environment, considering the implementation of functionality through several distributed components and services. • Work with our stakeholders to translate product goals into actionable engineering plans.