Senior Machine Learning Engineering, Trust
Airbnb
Senior Machine Learning Engineering, Trust
Job Description
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 Senior Machine Learning Engineer you are eager to understand complex systems top to bottom and thrive working across technologies and codebases. The Difference You Will Make: Everyone at Airbnb thinks about trust, but our team obsesses over it daily. At the core of trust is safety, and thus we spend a significant amount of our time and energy keeping the community safe. The Trust team is responsible for protecting our community and platform from fraud while also ensuring our hosts, guests, homes, and experiences meet our high standards. We constantly work to fight against online fraud (such as monetary loss, compromised accounts, spam and scam in messages, fake inventory, etc.) as well as offline fraud (theft, property damage, personal safety, etc.). We also work on onboarding and screening of users, and think about complex topics like identity and reputation to ensure that every interaction with Airbnb helps build trust in us and our community. Trust Engineering is responsible for the technology vision and development of a complex stack that runs on every key interaction on the platform.
A Typical Day
- 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.
- 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.
- Work closely with other trust defense and platform teams to tackle the changing landscape of fraud attacks.
- Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
- Examples include: Anomaly detection models, ML models for continuous risk evaluation.
Your Expertise
- 5+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields.
- Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models.
- Exposure to architectural patterns of a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models).
- Experience with test driven development, familiar with A/B testing, incremental delivery and deployment.
- Experience with the Trust and Risk domain is a plus.
Benefits
- bonus
- equity
- benefits
- Employee Travel Credits
How We'll Take Care of You
$191,000—$223,000 USD
Locations
- United States,
Salary
191,000 - 223,000 USD / yearly
191,000 - 223,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Strong programming (Scala / Python / Java/ C++ or equivalent) and data engineering skills.intermediate
- 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, computer vision, personalization and recommendation, anomaly detection).intermediate
- Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg. Hive).intermediate
Required Qualifications
- 5+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields. (experience)
- Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models. (experience)
- Exposure to architectural patterns of a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models). (experience)
- Experience with test driven development, familiar with A/B testing, incremental delivery and deployment. (experience)
- Experience with the Trust and Risk domain is a plus. (experience)
Responsibilities
- 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.
- 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.
- Work closely with other trust defense and platform teams to tackle the changing landscape of fraud attacks.
- Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
- Examples include: Anomaly detection models, ML models for continuous risk evaluation.
Benefits
- general: bonus
- general: equity
- general: benefits
- general: Employee Travel Credits
Tags & Categories
Answer 10 quick questions to check your fit for Senior Machine Learning Engineering, Trust @ Airbnb.
Related Books and Jobs
Senior Machine Learning Engineering, Trust
Airbnb
Senior Machine Learning Engineering, Trust
Job Description
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 Senior Machine Learning Engineer you are eager to understand complex systems top to bottom and thrive working across technologies and codebases. The Difference You Will Make: Everyone at Airbnb thinks about trust, but our team obsesses over it daily. At the core of trust is safety, and thus we spend a significant amount of our time and energy keeping the community safe. The Trust team is responsible for protecting our community and platform from fraud while also ensuring our hosts, guests, homes, and experiences meet our high standards. We constantly work to fight against online fraud (such as monetary loss, compromised accounts, spam and scam in messages, fake inventory, etc.) as well as offline fraud (theft, property damage, personal safety, etc.). We also work on onboarding and screening of users, and think about complex topics like identity and reputation to ensure that every interaction with Airbnb helps build trust in us and our community. Trust Engineering is responsible for the technology vision and development of a complex stack that runs on every key interaction on the platform.
A Typical Day
- 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.
- 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.
- Work closely with other trust defense and platform teams to tackle the changing landscape of fraud attacks.
- Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
- Examples include: Anomaly detection models, ML models for continuous risk evaluation.
Your Expertise
- 5+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields.
- Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models.
- Exposure to architectural patterns of a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models).
- Experience with test driven development, familiar with A/B testing, incremental delivery and deployment.
- Experience with the Trust and Risk domain is a plus.
Benefits
- bonus
- equity
- benefits
- Employee Travel Credits
How We'll Take Care of You
$191,000—$223,000 USD
Locations
- United States,
Salary
191,000 - 223,000 USD / yearly
191,000 - 223,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Strong programming (Scala / Python / Java/ C++ or equivalent) and data engineering skills.intermediate
- 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, computer vision, personalization and recommendation, anomaly detection).intermediate
- Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg. Hive).intermediate
Required Qualifications
- 5+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields. (experience)
- Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models. (experience)
- Exposure to architectural patterns of a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models). (experience)
- Experience with test driven development, familiar with A/B testing, incremental delivery and deployment. (experience)
- Experience with the Trust and Risk domain is a plus. (experience)
Responsibilities
- 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.
- 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.
- Work closely with other trust defense and platform teams to tackle the changing landscape of fraud attacks.
- Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
- Examples include: Anomaly detection models, ML models for continuous risk evaluation.
Benefits
- general: bonus
- general: equity
- general: benefits
- general: Employee Travel Credits
Tags & Categories
Answer 10 quick questions to check your fit for Senior Machine Learning Engineering, Trust @ Airbnb.
Related Books and Jobs