Staff Machine Learning Engineer, Airbnb
Relevance Research
$212-270k
More information about location
Community marketplace for holiday accomodation
Job no longer available
Community marketplace for holiday accomodation
1001+ employees
Job no longer available
$212-270k
More information about location
1001+ employees
Company mission
To create a world where anyone can belong anywhere.
Role
Who you are
- Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience
- 15 years of technical experience in Applied Machine Learning inclusive MS or PhD in relevant fields, including producing code for a production system and shipping production systems
- Strong programming (Scala / Python / Java/ C++ or equivalent), data engineering skills and experience with 3 or more of these technologies: Tensorflow, PyTorch, Spark, Kafka
- Deep understanding of Machine Learning best practices (eg training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg natural language processing, computer vision, personalization and recommendation, anomaly detection)
- Experience with Machine Learning (AI/ML), including working with training models and developing existing model structures
- Experience with test driven development, familiar with A/B testing, incremental delivery and deployment
What the job involves
- As a senior technical individual contributor, you will bring a unique skill set and experience to our organization, lead the architecture and design of the Relevance Intelligence Platform product, and work to solve some of the broader technical challenges within the organization
- You will work both on the overall Relevance Intelligence Platform architecture and future vision for the business, but will also lend expertise to specific teams and deep dive into projects as needed
- Our engineering organization is one where we value everyone’s input and ideas. Although you will be at the Principal level, all individual contributors at Airbnb are Software Engineers, will be expected to be hands on, and contribute code
- Define overall technical architecture for major parts of the Relevance Intelligent Platform and Product
- Architect large scale reliable Advanced AI/ML Based systems to support continuous growth of the business
- Influence the organization, engineering leaders, product managers, and the business to develop a unified approach to Intelligence Platforms at Airbnb
- Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases
- Understand how key technical decisions will drive business outcomes
- Perform design and code reviews and advice/mentor other AI/ML engineers at Airbnb
- Champion the best AI/ML engineering practices and build the engineering excellence culture in the organization
- Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact
- Hands-on develop, productionize, and operate Machine Learning 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
- Example projects include: feature platform, model interpretability, hyperparameter optimization, concept drift detection
Our take
When Airbnb was originally founded, the product helped customers book air mattresses on people's apartment floors. Since then, Airbnb has had over a billion customers hosted through its platform. With more than 4 million registered hosts worldwide, it has grown into a major player in the hospitality sector.
Airbnb has been successful in disrupting the traditional holiday lettings sector. Before it existed accommodation was limited to hotels and bed and breakfasts, but Airbnb has mainstreamed the idea of renting out spare rooms or even entire homes. It has created a new sector of hosts purchasing properties to rent out on the platform and provides a level of flexibility and a range of offerings not previously possible for travelers.
Perhaps a victim of its own success, by 2022 supply of Airbnb-listed properties began to outstrip demand in some markets, as hosts overestimated the appetite for domestic travel. However, the company is still posting strong financials and has unveiled new tools to support its hosts in a tougher rental market. With a healthy bottom line and a huge user base, Airbnb is very likely to overcome the current market turbulence and continue its growth.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Few candidates hear
back within 2 weeks
25% employee growth in 12 months
Company
Funding (last 2 of 10 rounds)
Apr 2020
$500m
GROWTH EQUITY VC
Mar 2017
$447.8m
SERIES F
Total funding: $3.8bn
Company benefits
- Paid volunteer time
- Health food and snacks
- Generous parental and family leave
- Learning and development
- Annual travel and experiences credit
Company values
- Champion the Mission: We’re united with our community to create a world where anyone can belong anywhere
- Be a Host: We're caring, open, and encouraging to everyone we work with
- Embrace the Adventure: We’re driven by curiosity, optimism, and the belief that every person can grow
- Be a Cereal Entrepreneur: We’re determined and creative in transforming our bold ambitions into reality
Company HQ
Showplace Square, San Francisco, CA
Articles
Leadership
Brian Chesky
(Co-Founder & CEO)Previously an Industrial Designer, studying at Rhode Island School of Design.
Nathan Blecharczyk
(Co-Founder & CSO)Studied Computer Science at Harvard, and had around 4 years of professional Software Engineering experience before founding Airbnb, including interning at Microsoft.
Joe Gebbia
(Co-Founder)Also studied Industrial Design at Rhode Island, and previously founded various design-related startups
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