Senior ML Platform Engineer
TRM LabsFull Time
Senior (5 to 8 years)
Candidates should have 3+ years of experience in infrastructure/platform engineering or large-scale distributed systems. A minimum of 2 years of hands-on experience with SQL-based cloud data warehouses such as BigQuery, Snowflake, Redshift, or Databricks is required. Proficiency with large-scale feature computation frameworks like Spark, PySpark, or Scala, and expertise in distributed systems including scaling, partitioning, fault tolerance, and caching are essential. Familiarity with ML production systems, particularly ML feature platforms, and knowledge of MLOps workflows are considered a significant advantage.
The Software Engineer will design and build data infrastructure for large-scale feature computation, transformation, and storage. They will develop frameworks for batch and event-driven features, focusing on reliability, scalability, and ease of use. Responsibilities include driving improvements in data quality and governance through validation, anomaly detection, drift monitoring, and feature lineage tracking. The engineer will also partner with ML engineers for seamless integration of feature engineering workflows, contribute to training set generation pipelines, and explore next-generation capabilities like streaming feature management.
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