Staff Machine Learning Engineer, AI Translation

Reposted Yesterday
Hiring Remotely in United States
Remote
204K-255K Annually
Expert/Leader
Real Estate • Travel • PropTech
The Role
As a Staff ML Engineer, you will develop and deploy machine translation models, collaborating across teams to enhance Airbnb's translation capabilities and improve global guest experiences.
Summary Generated by Built In

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:

As a Staff ML Engineer on the Translation AI team, you will play a critical role in accelerating the development and deployment of Translation AI at Airbnb. Machine Translation is critical to Airbnb, as we operate on a global scale and in the travel domain it is critical to ensure our guests and hosts can communicate across languages effectively. 

The Difference You Will Make:

Translation improves the international guest booking experience, enables seamless communication between hosts and guests, and reduces barriers for global travelers. You’ll work directly with product teams to deliver core Translation capabilities to power their product use cases. You’ll work closely with the ML Infrastructure engineering team to ensure the efficiency of our machine Translation and co-creating technology that will benefit all AI use cases. Come build the future of AI at Airbnb.

A Typical Day: 

  • Collaborate closely with teams across Airbnb—such as Customer Support, Guest & Host Tools, etc. — to deliver powerful machine translation capabilities for the entire company. Partner with teams to identify and prioritize translation-related challenges and opportunities.
  • Design and implement scalable machine translation models to improve accuracy and reduce cost and latency for Airbnb’s global platform.
  • Develop tooling, pipelines, and low level infrastructure (in collaboration with the ML Infrastructure team) that ensures we have a flexible foundation for machine translation spanning data preparation, evaluation, model selection / training, and inference.
  • Work with cutting-edge open-source models including Llama, as well as commercial Translation offerings.

Your Expertise:

  • 9+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields.
  • Strong programming (Scala / Python / Java / C++ or equivalent) and data engineering skills.
  • Deep familiarity with machine learning development practices, especially for language modeling & NLP applications.
  • Prior experience with deploying or supporting production ML systems at large scale - including operational experience on observability, continuous evaluation and improvement, progressive rollouts.
  • Familiarity with OSS tools and technologies such as: PyTorch, LlamaFactory, HuggingFace, NVidia Triton / TRTLLM, Ray.
  • Passionate about GenAI with a strong grasp of current trends in LLMs and related technologies. Deep understanding of GenAI models and their strengths/weaknesses, and ability to define the criteria for the right models/technologies to use to balance tradeoffs between quality, cost, performance, ease of operation and extensibility.
  • Strong communication and cross-team collaboration skills.
  • You may currently hold titles such as ML Engineer, Applied Scientist, or Data Scientist.

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: [email protected]. 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
$204,000$255,000 USD

Top Skills

C++
Huggingface
Java
Llamafactory
Nvidia Triton
Python
PyTorch
Ray
Scala
Trtllm
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The Company
HQ: Dublin
14,622 Employees
Year Founded: 2008

What We Do

Airbnb is a community based on connection and belonging—a community that was born in 2008 when two hosts welcomed three guests to their San Francisco home, and has since grown to 4 million hosts who have welcomed over 800 million guest arrivals to about 100,000 cities in almost every country and region across the globe. Hosts on Airbnb are everyday people who share their worlds to provide guests with the feeling of connection and being at home. At Airbnb, we believe that hosts, guests and the communities where we operate are all stakeholders we have a responsibility to serve, and that by serving them alongside our employees and investors, we will build an enduringly successful company.

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