Minimum QualificationsBachelor's degree or above in Computer Science, Engineering, Statistics, or related field.5+ years of professional software development experience using at least two general‑purpose languages (e.g., Java, C++, Python, C#).5+ years architecting, designing, and building multi‑component ML platforms leveraging open‑source/cloud‑agnostic components:Search/vector: ElasticSearch, Qdrant (as applicable to ML features and retrieval)Data warehouse/lakehouse: Snowflake; familiarity with Parquet/Delta/IcebergStreaming: Kafka; plus Flink/Spark Streaming experienceDatastores: PostgreSQL; NoSQL (MongoDB, Cassandra)Distributed compute: Spark, RayWorkflow orchestration: Airflow, Temporal5+ years managing end‑to‑end SDLC for ML systems: version control, CI/CD, Kubernetes, testing (unit/integration/data/ML eval), monitoring/alerting, production support.5+ years working with cloud providers (Azure and/or AWS) in production ML contexts. Lead design and implementation of models across classical ML and deep learning (e.g., gradient‑boosted trees, sequence models, Transformers for tabular/time‑series/NLP where relevant).Translate business goals into measurable ML objectives and experiment plans; ensure robust offline metrics and real‑world impact.