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# Senior Staff Machine Learning Engineer, Growth Platform Engineering

- **Company:** Airbnb
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Airflow, Software Applications, Architectural Patterns, Artificial Neural Networks, Computer Vision, C++ (Programming Language), Computer Programming, Information Engineering, Push Technology, Python (Programming Language), Machine Learning, Natural Language Processing, Software Product Management, Tensorflow, Azure Machine Learning, Unstructured Data, Feature Engineering, Boosted Trees, Pytorch, Multi-Agent Systems, Deep Learning, Agentic-AI, Kubernetes, Apache Kafka, Machine Learning Operations, Virtual Agents, Data Pipelines
- **Published:** October 22, 2026
- **Apply:** https://www.thejobnetwork.com/job/d3af31cf-a64d-49c8-a11b-60b56071e006/senior-staff-machine-learning-engineer-growth-platform-engineering

## About the Role

- 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)
, - **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

**Your Location:**



## Description

- We're seeking a **Senior Staff Engineer** who thrives at the intersection of **technical**  **depth** , **architectural**  **thinking** , and **mentorship**.
- You'll collaborate with cross-functional leaders, build resilient systems that operate globally at scale, and help evolve the foundational building blocks behind AI-powered growth systems.

Some example projects you will work on:

- **AI-Powered Content Generation** - Developing agentic capabilities to autonomously create personalized emails, push notifications, Ad copy, and creatives. This significantly scales marketing efforts by enabling more campaigns, greater variant testing, and faster iteration cycles.
- **ML/AI Orchestration for Decisioning** - Utilizing AI to determine the optimal audience, message, channel, and timing for communications. This shifts marketing decision-making to model-driven intelligence, enhancing relevance and minimizing message fatigue. The direct impact is an uplift in engagement rates, conversion, and ultimately, bookings.
- **Proactive Marketing Analyst Agent** - Designing an AI agent that autonomously identifies new marketing opportunities and converts them into executable campaigns. It leverages world knowledge, proprietary Airbnb intelligence, and deep customer profiles. A crucial performance-based feedback loop ensures the system continuously learns from campaign outcomes to refine and improve future recommendations.

**A Typical Day:**

- 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.

**Your Expertise:**