Senior Software Engineer, AI/ML
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Job Description
Senior AI/ML Software Engineer building scalable fraud detection and trust systems for Airbnb’s global hosting marketplace. Productionizing machine learning pipelines across batch and real-time use cases.
Responsibilities:
- Build and continuously improve novel ML systems, product integrations, and performance optimizations using large-scale structured and unstructured data
- Identify opportunities for business impact and refine and prioritize AI/ML model requirements with cross-functional partners
- Drive engineering decisions and quantify impact
- Collaborate with software engineers, product managers, operations, data scientists, trust defense teams, and platform teams
- Tackle changing fraud attack landscapes
- Productionize and operate AI/ML solutions and pipelines at scale for batch and real-time use cases
- Lead, mentor, challenge, and grow an enthusiastic, collaborative AI/ML culture
- Strengthen Airbnb’s Trust defenses and develop scalable solutions for online and offline risk
Requirements:
- 7+ years of industry experience in backend/platform engineering (or equivalent)
- BE/B.Tech, preferably in CS, or equivalent qualification
- Strong programming skills in Python, Java, or equivalent
- Data structures and algorithms knowledge
- Solid data engineering foundations
- Understanding of ML best practices, including training/serving skew minimization, A/B testing, feature engineering, and feature/model selection
- Knowledge of ML algorithms including gradient boosted trees, neural networks/deep learning, and optimization
- Knowledge of ML domains including natural language processing, computer vision, personalization and recommendation, and anomaly detection
- Experience with 3 or more of TensorFlow, PyTorch, Kubernetes, Spark, Airflow/Kubeflow, Kafka/Spark/Ray, and Hive
- Experience building observability for AI systems with metrics, logging, traces, automated alerting, dashboards, and SLO management
- Must have experience working in large tech product companies solving real-world problems
- Exposure to architectural patterns of large, high-scale software applications
- Experience with test-driven development, A/B testing, incremental delivery, and deployment
- Applied machine learning experience is a plus
- Experience building end-to-end machine learning infrastructure and/or productionizing machine learning models is a plus
- Experience with the Trust and Risk domain is a plus
Benefits:
- Bonus or incentives eligibility
- One or more equity programs
- Benefits
- Employee Travel Credits
- Allowances included in the base pay range
- Disability-inclusive application and interview process
- Reasonable accommodations during recruiting
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