Senior ML Platform Engineer

Candidates should possess strong general engineering skills with proficiency in Python, and experience across the entire spectrum of data engineering, including data stores like ClickHouse, ElasticSearch, Postgres, Redis, and Neo4j. Experience with data pipeline and workflow orchestration tools such as Airflow, DBT, Luigi, Azkaban, and Storm, as well as data processing technologies and streaming workflows like Spark, Kafka, and Flink is required. Proficiency in deployment and monitoring infrastructure in public cloud platforms including Docker, Terraform, Kubernetes, and Datadog, along with experience in loading, querying, and transforming large datasets, and familiarity with AI and ML integration tools like MLflow, Feast, ONNX, and Apache Beam are essential. The ideal candidate is comfortable working with noisy, dirty, and unstructured data, demonstrates a high degree of initiative and ownership, can navigate ambiguity, and possesses an exceptional ability to structure problems and prioritize critical issues. Strong communication skills for conveying complex ideas to diverse audiences and experience in collaborative, cross-functional environments are also necessary. A passion for building a safer financial system and an interest in virtual currencies and blockchain analysis are a plus.