Staff Machine Learning Engineer, Relevance and Personalization

Airbnb

Staff Machine Learning Engineer at Airbnb working on search and recommendation algorithms. Collaborating with cross-functional teams on impactful AI technologies within a remote environment.

Posted 5/18/2026full-timeRemote • 🇺🇸 United StatesLead💰 $212,000 - $265,000 per yearWebsite

Tech Stack

Tools & technologies

AirflowJavaKafkaKubernetesPythonPyTorchScalaSparkTensorflow

About the role

Key responsibilities & impact

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.
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.

Requirements

What you’ll need

9+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields.
Strong programming (Scala / Python / Java / C++ or equivalent) and data engineering skills.
Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg. neural networks/deep learning, optimization) and domains (eg. natural language processing, computer vision, personalization, search and recommendation, marketplace optimization, anomaly detection).
Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg. Hive).
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.

Benefits

Comp & perks

bonus
equity
benefits
Employee Travel Credits

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Machine LearningScalaPythonJavaC++TensorflowPyTorchKubernetesSparkAirflow

Soft Skills

collaborationcommunicationproblem-solvingprioritizationengineering decision-making

Certifications

MS in relevant fieldsPhD in relevant fields