Senior Machine Learning Engineer

What you'll do

• Build and maintain high-throughput batch and streaming data pipelines for ML and real-time decisioning.
• Implement data ingestion, enrichment, aggregation, and transformation workflows using distributed data frameworks.
• Develop and operate systems for real-time feature computation and delivery for online ML services.
• Build and operate ML-adjacent services including inference inputs, feature APIs, and data access layers.
• Instrument data and ML infrastructure with metrics, logging, and alerting to support production operations.
• Participate in on-call rotations and incident response for data and ML platforms.
• Identify and remediate data pipeline failures, performance regressions, and operational risks.
• Collaborate with data science teams to enable production ML workflows through reliable data systems.

What we're looking for

• Experience building and operating large-scale data or ML systems in production.
• Strong fundamentals in distributed systems and data processing architectures.
• Hands-on experience with streaming and batch data technologies like Kafka, Kinesis, Spark, or Flink.
• Proficiency in Python and working knowledge of Java, Scala, Go, or C++.
• Experience operating systems in cloud-native environments using AWS, containers, Kubernetes, and IaC tools.
• Familiarity with observability and operational best practices for production systems.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or a related field.
• 5+ years of industry experience building data-intensive or ML-adjacent systems in production.