Machine Learning Engineer, Core ML
Seattle, San Francisco, United States
What is Core Machine Learning at Airbnb?
The Core Machine Learning (Core ML) Team is focused on creating state of the art Machine Learning systems that help Airbnb products scale and become intelligent. We use data-driven approach to solve problems and follow up closely with the research community to learn cutting-edge ML techniques. We are constantly faced with challenges at industrial scale such as Natural Language Processing (NLP), Personalization, Information Retrieval, Relevance Ranking and are pushing the boundary of how Airbnb thinks of its data.
About the Role:
As a Machine Learning Engineer on Core ML and part of the Community Support Platform (CSP) team, you will have the unique opportunity for massive impact given that you’ll directly drive what is the brain and intelligent backbone of projects that will enable automation and accurate prediction in a scalable way, reduce cost, improve user experience and stimulate sustainable growth. You’ll influence key strategic decisions across all Airbnb product teams by bringing data and insights to the table. You'll be in the driver seat to change Airbnb’s DNA around defect reduction using data to drive forward our vision of a world where guests and hosts can use our products seamlessly.
We have a strong team of Machine Learning Engineers, our work is highly sought-after, and our impact on the business is tremendous. If you have a proven background in this field and are excited to help build Airbnb’s community, we want to hear from you.
- Defining, modeling and solving real, challenging problems using a data-driven approach and expertise in Machine Learning.
- Identify and set up data labeling tasks, write robust labeling guidelines whenever data collection is needed. Also evaluate labeling quality and collaborate with labelers to address their feedback.
- Determine model offline and online metrics for measuring success. Creating online A/B test experiments and constantly monitor its performance before launch.
- Build, test, implement your model into production with engineering quality and long term design trade-offs in mind.
- Ability to identify problems and scope opportunities into large projects with PMs, Data scientists and other colleagues to deliver impact.
- Keep improving the quality and performance of models continuously if necessary. Keeping up with the state of the art performances by attending conferences and reading paper.
- Conceptualizing, developing, and maintaining dashboards and visualizations for models in production, if necessary
- 4+ years professional experience, or PhD in a quantitative field including Computer Science, Physics, Applied Math, Statistics or other highly quantitative fields.
- Quality in systems designs, coding styles and implementation.
- Experience with languages used for Machine Learning experiment/implementation such as Python and frameworks like PyTorch and TensorFlow.
- Experience of languages used in production for integration such as Java is a plus.
- Experience or willingness to learn the state of the art NLP models such as the Transformer family, cross-lingual representation for both short and long texts.
- Experience or willingness to learn state of the art Deep Learning paradigms and application of them into areas such as Text Classification, Semantic Modeling, Ranking and Personalization.
- Understanding of analytics & experimentation
- Ability to communicate clearly and to effectively influence others
- Competitive salaries
- Quarterly employee travel coupon
- Paid time off
- Medical, dental, & vision insurance
- Life insurance and disability benefits
- Fitness Discounts
- Flexible Spending Accounts
- Apple equipment
- Community Involvement (4 hours per month to give back to the community)
- Much more…