Senior Staff Machine Learning Engineer, Growth Platform Engineering

🕒 April 15

🇺🇸 United States – Remote

💵 $244k - $305k / year

⏰ Full Time

🟠 Senior

🏗️ Platform Engineer

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Airbnb

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2007

✈️ Travel

📦 Logistics

🛍️ eCommerce

💰 Post-IPO Equity on 2020-12

Travel • Logistics • eCommerce

Airbnb is a global online marketplace that connects people looking for accommodation with hosts offering unique and diverse lodging options, often in residential properties. Users can book spaces ranging from one-bedroom apartments to entire homes and boutique hotels. Airbnb also offers experiences, allowing guests to book activities hosted by locals, providing an authentic travel experience.

📋 Description

• As a machine learning engineer or scientist, your expertise will be pivotal in developing AI-powered solutions to shape the future of the Airbnb agentic growth platform with cutting-edge AI techniques. You will drive and guide the rest of the engineers to brainstorm, design and develop AI products and features from inception to production. • Collaborate with cross-functional leaders, build resilient systems that operate globally at scale, and help evolve the foundational building blocks behind AI-powered growth systems. • Work with large scale structured and unstructured data; explore, experiment, build and continuously improve Machine Learning models and pipelines for Airbnb product, business and operational use cases. • Work collaboratively with cross-functional partners including product managers, operations and data scientists, to identify opportunities for business impact; understand, refine, and prioritize requirements for machine learning, and drive engineering decisions. • Hands-on develop, productionize, and operate ML/AI models and pipelines at scale, including both batch and real-time use cases. • Leverage third-party and in-house Machine Learning tools & infrastructure to develop reusable, highly differentiating and high-performing Machine Learning systems, enable fast model development, low-latency serving and ease of model quality upkeep. • Collaborate actively with engineers to apply ML / AI in their solutions to help validate ideas and guide to the right outcomes. • Partner with ML/AI Engineers in foundations engineering to mentor and develop initiatives that make ML/AI applications a core discipline for non-ML/AI engineers.

🎯 Requirements

• 12+ years of industry experience in applied ML/AI, inclusive MS or PhD in relevant fields • Strong programming (Scala / Python / Java / C++ or equivalent) and data engineering skills • Deep understanding of ML/AI best practices (e.g. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (e.g. neural networks/deep learning, optimization) and domains (e.g. natural language processing, computer vision, personalization, search and recommendation, marketplace optimization, anomaly detection) • Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection) and algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization) • Experience with technologies such as: Tensorflow, PyTorch, Kubernetes, Airflow (or equivalent), Kafka (or equivalent) • Expertise with architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models) • Agentic and Automation: Experience with AI technologies in automating processes and developing agentic solutions and frameworks. • Agile Practice for AI Production: Experience with the entire AI product development lifecycle from incubation to production at scale, following agile practices in the Applied AI/ML domain. • Infrastructure Acumen: Experience building robust testing frameworks for agent behavior validation and continuous improvement, and driving architectural requirements on ML infrastructures.

🏖️ Benefits

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