Staff Machine Learning Engineer, Payments
Airbnb
Staff Machine Learning Engineer, Payments
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: Payments is key for any healthy marketplace, and is just as central to our product at Airbnb. The Payments org at Airbnb is responsible for everything related to settling money in Airbnb’s global marketplace and makes the Payment experience as delightful, magical, intuitive, and easy as possible. At the Payments modeling team, our goal is to empower the mission by introducing intelligences and personalizations that optimize Airbnb’s massive daily transaction volume to best collect payments from guests, distribute payouts to hosts while preventing fraudulent transactions from happening. The Difference You Will Make: As a Staff ML Engineer for Payments, you will be the catalyst that transforms bold AI innovation — LLM-powered workflow, real-time fraud defenses, and hyper-personalized checkout flows — into production systems that make Airbnb Payment experience feel effortless and secure; you’ll architect and own end-to-end solutions at global scale, partner closely with product, software, and operations teams to turn complex requirements into elegant, latency-first services, and set the technical standard for model governance, continuous learning, and engineering excellence that elevates our entire payments ecosystem while shaping the company’s broader AI strategy.
A Typical Day
- Transform bold AI innovation — LLM-powered workflow, real-time fraud defenses, and hyper-personalized checkout flows — into production systems
- Architect and own end-to-end solutions at global scale
- Partner closely with product, software, and operations teams to turn complex requirements into elegant, latency-first services
- Set the technical standard for model governance, continuous learning, and engineering excellence
- Spearhead LLM agents, real-time anomaly detectors, and other breakthrough solutions
- Collaborate with product, engineering, ops, and data science to spot high-leverage opportunities, refine AI/ML requirements, make principled architecture choices, and measure business value
- Design, train, deploy, and operate large-scale AI applications for both batch and streaming workloads, ensuring low latency, high reliability, and continuous improvement
- Mentor and inspire teammates, fostering a collaborative, experimentation-driven environment
Your Expertise
- 9+ years of industry experience in applied AI/ML, inclusive MS or PhD in relevant fields
- Prior knowledge of AI/ML Applications in the Payments domain is highly desirable
Benefits
- Bonus
- Equity
- Benefits
- Employee Travel Credits
How We'll Take Care of You
$204,000—$255,000 USD
Locations
- United States,
Salary
204,000 - 255,000 USD / yearly
204,000 - 255,000 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 (Python/Java) and data engineering skillsintermediate
- Proven mastery of modern AI/LLM workflows — prompt engineering, fine-tuning (LoRA, RLHF), hallucination mitigation, safety guardrails, and rigorous online/offline testingintermediate
- Hands-on experience with at least three of the following: PyTorch/TensorFlow, scalable inference stacks (Triton, vLLM), vector search, orchestration/MLOps platforms (Kubeflow, Airflow), large-scale data streaming & processing (Spark, Ray, Kafka)intermediate
- Demonstrated success designing, deploying, and monitoring production AI systems—e.g., RAG pipelines, personalization engines, generative content services—complete with drift/cost/latency monitoring, automated re-training triggers, and cross-functional collaborationintermediate
Required Qualifications
- 9+ years of industry experience in applied AI/ML, inclusive MS or PhD in relevant fields (experience)
- Prior knowledge of AI/ML Applications in the Payments domain is highly desirable (experience)
Responsibilities
- Transform bold AI innovation — LLM-powered workflow, real-time fraud defenses, and hyper-personalized checkout flows — into production systems
- Architect and own end-to-end solutions at global scale
- Partner closely with product, software, and operations teams to turn complex requirements into elegant, latency-first services
- Set the technical standard for model governance, continuous learning, and engineering excellence
- Spearhead LLM agents, real-time anomaly detectors, and other breakthrough solutions
- Collaborate with product, engineering, ops, and data science to spot high-leverage opportunities, refine AI/ML requirements, make principled architecture choices, and measure business value
- Design, train, deploy, and operate large-scale AI applications for both batch and streaming workloads, ensuring low latency, high reliability, and continuous improvement
- Mentor and inspire teammates, fostering a collaborative, experimentation-driven environment
Benefits
- general: Bonus
- general: Equity
- general: Benefits
- general: Employee Travel Credits
Tags & Categories
Answer 10 quick questions to check your fit for Staff Machine Learning Engineer, Payments @ Airbnb.
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Staff Machine Learning Engineer, Payments
Airbnb
Staff Machine Learning Engineer, Payments
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: Payments is key for any healthy marketplace, and is just as central to our product at Airbnb. The Payments org at Airbnb is responsible for everything related to settling money in Airbnb’s global marketplace and makes the Payment experience as delightful, magical, intuitive, and easy as possible. At the Payments modeling team, our goal is to empower the mission by introducing intelligences and personalizations that optimize Airbnb’s massive daily transaction volume to best collect payments from guests, distribute payouts to hosts while preventing fraudulent transactions from happening. The Difference You Will Make: As a Staff ML Engineer for Payments, you will be the catalyst that transforms bold AI innovation — LLM-powered workflow, real-time fraud defenses, and hyper-personalized checkout flows — into production systems that make Airbnb Payment experience feel effortless and secure; you’ll architect and own end-to-end solutions at global scale, partner closely with product, software, and operations teams to turn complex requirements into elegant, latency-first services, and set the technical standard for model governance, continuous learning, and engineering excellence that elevates our entire payments ecosystem while shaping the company’s broader AI strategy.
A Typical Day
- Transform bold AI innovation — LLM-powered workflow, real-time fraud defenses, and hyper-personalized checkout flows — into production systems
- Architect and own end-to-end solutions at global scale
- Partner closely with product, software, and operations teams to turn complex requirements into elegant, latency-first services
- Set the technical standard for model governance, continuous learning, and engineering excellence
- Spearhead LLM agents, real-time anomaly detectors, and other breakthrough solutions
- Collaborate with product, engineering, ops, and data science to spot high-leverage opportunities, refine AI/ML requirements, make principled architecture choices, and measure business value
- Design, train, deploy, and operate large-scale AI applications for both batch and streaming workloads, ensuring low latency, high reliability, and continuous improvement
- Mentor and inspire teammates, fostering a collaborative, experimentation-driven environment
Your Expertise
- 9+ years of industry experience in applied AI/ML, inclusive MS or PhD in relevant fields
- Prior knowledge of AI/ML Applications in the Payments domain is highly desirable
Benefits
- Bonus
- Equity
- Benefits
- Employee Travel Credits
How We'll Take Care of You
$204,000—$255,000 USD
Locations
- United States,
Salary
204,000 - 255,000 USD / yearly
204,000 - 255,000 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 (Python/Java) and data engineering skillsintermediate
- Proven mastery of modern AI/LLM workflows — prompt engineering, fine-tuning (LoRA, RLHF), hallucination mitigation, safety guardrails, and rigorous online/offline testingintermediate
- Hands-on experience with at least three of the following: PyTorch/TensorFlow, scalable inference stacks (Triton, vLLM), vector search, orchestration/MLOps platforms (Kubeflow, Airflow), large-scale data streaming & processing (Spark, Ray, Kafka)intermediate
- Demonstrated success designing, deploying, and monitoring production AI systems—e.g., RAG pipelines, personalization engines, generative content services—complete with drift/cost/latency monitoring, automated re-training triggers, and cross-functional collaborationintermediate
Required Qualifications
- 9+ years of industry experience in applied AI/ML, inclusive MS or PhD in relevant fields (experience)
- Prior knowledge of AI/ML Applications in the Payments domain is highly desirable (experience)
Responsibilities
- Transform bold AI innovation — LLM-powered workflow, real-time fraud defenses, and hyper-personalized checkout flows — into production systems
- Architect and own end-to-end solutions at global scale
- Partner closely with product, software, and operations teams to turn complex requirements into elegant, latency-first services
- Set the technical standard for model governance, continuous learning, and engineering excellence
- Spearhead LLM agents, real-time anomaly detectors, and other breakthrough solutions
- Collaborate with product, engineering, ops, and data science to spot high-leverage opportunities, refine AI/ML requirements, make principled architecture choices, and measure business value
- Design, train, deploy, and operate large-scale AI applications for both batch and streaming workloads, ensuring low latency, high reliability, and continuous improvement
- Mentor and inspire teammates, fostering a collaborative, experimentation-driven environment
Benefits
- general: Bonus
- general: Equity
- general: Benefits
- general: Employee Travel Credits
Tags & Categories
Answer 10 quick questions to check your fit for Staff Machine Learning Engineer, Payments @ Airbnb.
Related Books and Jobs