This role pays less than
72%
of similar roles. Most pay
$201,150–$254,750
— the shaded band above.
At the midpoint, this role pays about
$207k
versus about
$228k
for comparable roles.
Based on 240 similar postings.
Employer
About Airbnb
Founded in 2008 and formerly known as AirBed & Breakfast, Inc., Airbnb is a global marketplace connecting travelers with hosts who offer unique accommodations, ranging from private rooms to entire homes. It operates a massive digital platform for booking stays, experiences, and travel services worldwide.
Airbnb currently has
65 open roles
on FindRole.
Listed pay typically runs
$200,000–$240,000
across 51 roles with salary data.
Senior Machine Learning Engineer, Payments joins the Payments modeling team to optimize massive transaction volumes by implementing intelligent systems for payment collection, host payouts, and fraud prevention. You will architect and own end-to-end production solutions, including LLM-powered workflows, real-time anomaly detectors, and hyper-personalized checkout flows. The role involves designing, training, and operating large-scale AI applications for batch and streaming workloads while ensuring low latency and high reliability through automated monitoring and retraining loops. You will utilize Python, Java, PyTorch, TensorFlow, Spark, Ray, Kafka, and MLOps platforms like Kubeflow or Airflow. Key technical competencies include prompt engineering, fine-tuning via LoRA and RLHF, hallucination mitigation, and vector search. This role addresses critical payment infrastructure challenges by transforming complex requirements into scalable services that ensure a secure and seamless transaction experience within the global marketplace.
What does a Machine Learning Engineer earn in Remote?
Median $229700 from 72 postings across 27 companies.
Develop LLM-powered workflows and real-time fraud detection systems to secure the payments ecosystem.
Architect and own end-to-end AI solutions that handle high transaction volumes at a global scale.
Design, train, and deploy large-scale AI applications for both batch and streaming workloads.
Ensure low-latency performance and reliability through automated monitoring and retraining loops.
Translate complex business requirements into technical specifications for personalized checkout flows.
Implement model governance standards to manage hallucination mitigation, safety guardrails, and inference drift.
Mentor team members to foster an experimentation-driven environment focused on production excellence.
What we're looking for
Must have 5+ years of industry experience in applied AI/ML.
Must possess an MS or PhD in a relevant field.
Must have strong programming skills in Python and Java.
Must have data engineering skills.
Must demonstrate mastery of modern AI/LLM workflows including prompt engineering, fine-tuning, and hallucination mitigation.
Must have hands-on experience with at least three: PyTorch/TensorFlow, scalable inference stacks, vector search, MLOps platforms, or large-scale data streaming.
Must have experience designing, deploying, and monitoring production AI systems for batch and streaming workloads.
Prior knowledge of AI/ML applications in the payments domain is highly desirable (preferred).
Generative AI
LLM
PyTorch
Python
Machine Learning
RAG
Reinforcement Learning
Model Quantization
GPU Inference
Data Processing
multimodal modeling
Kernel Development
Machine Learning
LLMs
GenAI
Agentic AI
Python
Scala
Java
C++
TensorFlow
PyTorch
Kubernetes
Data Engineering
Natural Language Processing
Computer Vision
Anomaly Detection
A/B Testing
Test Driven Development