• Design and build intelligent copilot experiences that help human agents resolve cases faster • Develop systems to detect and handle bad actors • Own key components of our multi-agent framework from design through production • Develop robust, well-tested Python applications • Contribute to best practices for system design, coding standards, and evaluation frameworks • Partner with Product, CX, and Security stakeholders through design reviews

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 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: - Trust is essential to the success of the Airbnb platform for both guests and hosts. The Safety team invests significant effort in keeping the community safe and building this trust. - We are responsible for detecting reservations with party intent that could violate Airbnb platform policies. Our goal is to block these users before check-in to prevent critical life safety incidents for our guests and hosts. The Difference You Will Make: - Guests provide signals about potential party intent during the booking process. Combining these signals with internally available data offers a significant opportunity to develop various heuristics and machine learning models to predict the likelihood of unauthorized parties. - As a Senior Machine Learning Engineer on the Trust & Safety team, you will collaborate with product managers, data scientists, designers, and customer service operations to innovate new ways to predict and prevent critical life safety and property damage incidents on the platform. - The problems you tackle will often be vague and ambiguous, requiring you to possess a strong curiosity to deeply investigate various user patterns and behaviors to understand how and where these life safety incidents might occur. A Typical Day: - 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. - Working together with a wide variety of business functions to stop critical life safety and property damage incidents in real time. - Creating new holistic machine learning model detection strategies by collaborating with other trust and safety prevention teams around the Trust 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 fraud detection and mitigation. - Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases. Your Expertise: - 5+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields - 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 (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization) and domains (eg. natural language processing, computer vision, personalization and recommendation, anomaly detection) - Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg. Hive) - Industry experience building end-to-end Machine Learning 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. Your Location: 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. Our Commitment To Inclusion & Belonging: Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply. We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application. How We'll Take Care of You: 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 $191,000—$223,000 USD

• Support ML Models deployment and ensure reliability • Enhance our client´s Marine-Operations Performance Monitoring & Forecasting capabilities • Work on mission-critical systems such as regression models for shipboard performance • Handle advanced fuel forecasting models • Strong software engineering, model packaging/deployment, configuration and ML skills

• Enhance Marine-Operations Performance Monitoring & Forecasting capabilities • Includes code refactoring and enhancements on a dynamic regression model • Creating an enhanced fuel forecasting model • Serving model through a Container App or Endpoint for Business Planning Teams.