Senior Software Engineer

• Work with large scale structured and unstructured data, build and continuously improve  novel ML systems, product integrations, and performance optimizations 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 AI/ML models, drive engineering decisions, and quantify impact.
• Work closely with other trust defense and platform teams to tackle the changing landscape of fraud attacks.
• Hands-on productionize, and operate  AI/ML solution and pipelines at scale, including both batch and real-time use cases.
• Lead, mentor, challenge and grow enthusiastic, collaborative AI/ML culture within the organization

Your Expertise:

• 7+ years of industry experience in backend/platform engineering (or equivalent) with BE/B.tech, preferably in CS, or equivalent qualification (experience in applied Machine Learning is a plus).
• Strong programming (Python / Java or equivalent), DSA plus solid data engineering foundations.
• Understanding of ML best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization) and domains (eg. natural language processing, computer vision, personalization and recommendation, anomaly detection)
• Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, orchestration (Airflow/Kubeflow), streaming/processing (Kafka/Spark/Ray), data warehouse (eg. Hive)
• Experience in building observability for AI systems (metrics/logging/traces), with automated alerting, dashboards, and SLO management.
• Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models is a plus.
• Must have experience working in large tech product companies solving real world problems.
• 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.
  • Experience with the Trust and Risk domain is a plus.