Airbnb Senior Machine Learning Engineer Quality Merchandising 

United States 

832564238

The Difference You Will Make:

We are seeking a highly skilled and motivated ML engineer who is looked up to as a ML modeling expert. We are at the early journey of building a company-wide user centric platform and products in a multi-year effort. As a technical leader, you will have the unique opportunity to drive multiple years of technical vision and architect an ML driven system which serves to provide intelligence for millions of listings quality and merchandising insights from scratch. You will be in charge of the whole lifecycle of big yet ambiguous problem solving from prototyping to leading a group of talented engineers to deliver high quality work through multiple releases.

A Typical Day:

• Provide critical input and be able to influence technical direction.
• Influence and collaborate with stakeholders to adopt team goals and roadmaps.
• Work with cross functional partners (product managers, DS, Analytics etc) to design and deliver high-quality systems.
• Design and implement ML models to drive organic bookings and improve user experience
• Lead efforts to architect, prototype, build and launch solutions for host or listing success.
• Mentor engineers on day to day basis to ensure quality and directions, both within and outside of the team

Your Expertise:

• 5+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields.
• Strong programming (Python/Java) 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, personalization and recommendation).
• 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 large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models).
• Prior knowledge of ML Applications in the ranking, recommendation or personalization domain is highly desirable

Offices: United States