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Salary: INR 4,500,000 - 6,500,000 / annual
Airbnb's Trust Engineering team is seeking a Senior Software Engineer specializing in AI/ML to help build and strengthen the platform's fraud detection and community safety systems. The Trust team is responsible for protecting the community from both online fraud (account compromise, spam, fake inventory, monetary loss) and offline fraud (theft, property damage, personal safety issues), as well as user onboarding, screening, identity verification, and reputation systems.
In this role, you will work with a talented team of software engineers to develop intuitive experiences, strengthen existing offerings, and deliver new products that enhance Airbnb's trust defenses. You'll play a significant role in shaping the technical vision and delivering flexible, efficient, and scalable solutions that adapt to evolving attack vectors.
Key responsibilities include:
- Working with large-scale structured and unstructured data to build and continuously improve novel ML systems, product integrations, and performance optimizations for business and operational use cases
- Collaborating cross-functionally with software engineers, product managers, operations, and data scientists to identify business impact opportunities, refine requirements, drive engineering decisions, and quantify impact
- Working closely with trust defense and platform teams to address the changing landscape of fraud attacks
- Hands-on productionization and operation of AI/ML solutions and pipelines at scale, including both batch and real-time use cases
- Leading, mentoring, and fostering an enthusiastic, collaborative AI/ML culture within the organization
Requirements:
- 7+ years of industry experience in backend/platform engineering (or equivalent) with BE/B.Tech degree, preferably in Computer Science or equivalent qualification (applied Machine Learning experience is a plus)
- Strong programming skills in Python, Java, or equivalent; solid data structures and algorithms knowledge plus strong 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 such as gradient boosted trees, neural networks/deep learning, and optimization techniques
- Familiarity with ML domains including natural language processing, computer vision, personalization, recommendation systems, and anomaly detection
- Experience with 3+ of the following technologies: TensorFlow, PyTorch, Kubernetes, Spark, orchestration tools (Airflow/Kubeflow), streaming/processing platforms (Kafka/Spark/Ray), or data warehouses (Hive)
- Experience building observability for AI systems including metrics, logging, traces, automated alerting, dashboards, and SLO management
- Industry experience building end-to-end ML infrastructure and/or productionizing ML models (preferred)
- Must have experience working in large tech product companies solving real-world problems
- Exposure to architectural patterns of large, high-scale software applications including well-designed APIs, high-volume data pipelines, efficient algorithms, and models
- Experience with test-driven development, A/B testing, incremental delivery, and deployment practices
- Experience in the Trust and Risk domain (preferred)
