Senior Machine Learning Engineer

Senior Machine Learning Engineer responsible for building and operating distributed data and ML infrastructure that supports high-throughput, low-latency data processing and real-time ML use cases. You will develop large-scale streaming data pipelines, real-time feature computation systems, ML-adjacent services, and ensure reliability, observability, and efficient collaboration with applied ML and data science teams. Core activities include implementing data ingestion, enrichment, and transformation workflows; maintaining feature stores and online/offline data consistency; building scalable service patterns with autoscaling and rollout strategies; instrumenting data and ML infrastructure with metrics, logging, and alerts; participating in design and code reviews to advance production-grade ML/data platforms. Required experience includes hands-on work with distributed data technologies (Kafka, Kinesis, Spark, Flink), proficiency in Python and at least one of Java/Scala/Go/C++, and cloud-native operations (AWS, containers, Kubernetes, IaC). Preferred qualifications cover real-time personalization, feature stores, event-driven architectures, and ML tooling for model lifecycle and experimentation.