# Senior Staff Machine Learning Engineer, Growth Platform Engineering

**Company:** [Airbnb](https://hotfix.jobs/companies/airbnb)
**Location:** Remote
**Role:** ML Engineering
**Salary:** $244k – $305k/yr
**Experience:** 12+ years
**Skills:** Machine Learning, Deep Learning, PyTorch, TensorFlow, Kubernetes, Airflow, Kafka, Python, Scala, Java, Natural Language Processing, Computer Vision, Gradient Boosted Trees, Feature Engineering, A/B Testing
**Posted:** 2026-04-14

> Develops and productionizes AI/ML models and pipelines at scale for Airbnb's agentic growth platform, powering personalized content generation, decisioning, and proactive marketing agents. Requires 12+ years experience, strong programming, and expertise in ML best practices and tools like PyTorch and Kubernetes.

## Job Description

## Responsibilities
- Work with large scale structured and unstructured data; explore, experiment, build and continuously improve Machine Learning models and pipelines for Airbnb product, business and operational use cases.
- Work collaboratively with cross-functional partners including product managers, operations and data scientists, to identify opportunities for business impact; understand, refine, and prioritize requirements for machine learning, and drive engineering decisions.
- Hands-on develop, productionize, and operate ML/AI 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.
- Collaborate actively with engineers to apply ML / AI in their solutions to help validate ideas and guide to the right outcomes.
- Partner with ML/AI Engineers in foundations engineering to mentor and develop initiatives that make ML/AI applications a core discipline for non-ML/AI engineers.

## Expertise
- 12+ years of industry experience in applied ML/AI, inclusive MS or PhD in relevant fields
- Strong programming (**Scala / Python / Java / C++** or equivalent) and data engineering skills
- Deep understanding of ML/AI best practices (e.g. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (e.g. neural networks/**deep learning**, optimization) and domains (e.g. **natural language processing**, **computer vision**, personalization, search and recommendation, marketplace optimization, anomaly detection)
- Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection) and algorithms (eg. gradient boosted trees, neural networks/**deep learning**, optimization)
- Experience with technologies such as: **Tensorflow**, **PyTorch**, **Kubernetes**, **Airflow** (or equivalent), **Kafka** (or equivalent)
- Expertise with architectural patterns of a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models)

## Preferred Qualifications
- Agentic and Automation: Experience with AI technologies in automating processes and developing agentic solutions and frameworks.
- Agile Practice for AI Production: Experience with the entire AI product development lifecycle from incubation to production at scale, following agile practices in the Applied AI/ML domain.
- Infrastructure Acumen: Experience building robust testing frameworks for agent behavior validation and continuous improvement, and driving architectural requirements on ML infrastructures

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