Manager, Machine Learning Engineering - Relevance and Personalization

Airbnb is a global platform that connects hosts and guests for unique stays and experiences. They are seeking a Machine Learning Engineering Manager to lead a team responsible for enhancing the discovery experience for users through the development of advanced machine learning models and algorithms. The role involves collaboration with cross-functional teams and focuses on delivering high-quality ML solutions at scale while fostering an inclusive team culture.

Responsibilities:

• Work with large scale structured and unstructured data, provide technical leadership to build and continuously improve cutting edge Machine Learning (ML) models for Airbnb product, business and operational use cases
• Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, set team priorities and roadmap, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact
• Lead the delivery of ML/AI models and pipelines at scale, including both batch and real-time use cases, ensuring operational excellence (on-call health, reliability, cost, latency, and model quality)
• Leverage third-party and in-house ML/AI 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, and drive adoption of best practices across the team
• Example projects include: feature platform, model interpretability, hyperparameter optimization, concept drift detection
• Hire, coach, and develop engineers; set clear expectations; conduct performance management; and build a strong, inclusive team culture

Requirements:

• 10+ years of industry experience in applied ML/AI, inclusive MS or PhD in relevant fields
• 3+ years of engineering management experience, with 8+ years of relevant software development industry experience in a fast paced tech environment
• Strong programming (Scala / Python / Java / C++ or equivalent) and data engineering skills, with demonstrated ability to guide design reviews and architecture decisions for ML systems
• 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) with the ability to translate technical tradeoffs into product and business outcomes
• Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (e.g. Hive)
• Industry experience building end-to-end ML/AI infrastructure and/or building and productionizing ML models, including leading multi-quarter initiatives and coordinating delivery across teams
• Exposure to architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models) and experience establishing engineering standards (reviews, testing, observability, incident response)
• Experience with test driven development, familiar with A/B testing, incremental delivery and deployment, and ability to create team processes that improve execution predictability and quality