Remote Senior ML Engineer, Payments — Real‑Time AI & Checkout

airbnb, Inc.; United States; À distance; USD 191 000 - 223 000; Plein temps

Résumé du poste

Airbnb, Inc. is seeking a Senior Machine Learning Engineer for Payments to lead AI initiatives across global transaction flows. This role focuses on building end-to-end ML systems, including LLM-powered workflows, real-time fraud defenses, and hyper-personalized checkout experiences.

The ideal candidate will own end-to-end solutions with latency-first design, collaborate with product and operations teams, and drive governance and continuous learning for the payments ecosystem.

Qualifications

• 5+ years of industry experience in applied AI/ML, with MS or PhD in relevant fields.
• Strong programming in Python/Java and data engineering skills.
• Proven mastery of modern AI/LLM workflows - prompt engineering, LoRA/RLHF, safety guardrails, testing.
• Hands-on with PyTorch/TensorFlow, scalable inference stacks, vector search, MLOps.
• Experience deploying production AI systems with monitoring, retraining, and cost/latency considerations.

Responsabilités

• Spearhead LLM agents, real-time anomaly detectors, and breakthrough AI solutions.
• Collaborate with product, engineering, ops, and data science to identify high-leverage AI opportunities.
• Design, train, deploy, and operate large-scale AI applications for batch and streaming workloads.
• Mentor teammates and foster a collaborative, experimentation-driven environment for production excellence.

Connaissances

Applied AI/ML

Python/Java

LLM workflows

PS PyTorch/TensorFlow

MLOps platforms

Data streaming

Payments domain knowledge

Formation

MS or PhD in relevant fields

Outils

Kubeflow

Airflow

Spark

Ray

Kafka

Vector search

Description du poste

Airbnb, Inc. is seeking a Senior Machine Learning Engineer for Payments to lead AI initiatives across global transaction flows. This role focuses on building end-to-end ML systems, including LLM-powered workflows, real-time fraud defenses, and hyper-personalized checkout experiences.

The ideal candidate will own end-to-end solutions with latency-first design, collaborate with product and operations teams, and drive governance and continuous learning for the payments ecosystem.