Middle to Senior ML Engineer

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• Build and maintain ML inference and feature engineering pipelines on Databricks
• Develop feature pipelines — transformations, aggregations, time-based features at scale using PySpark
• Deploy and manage models in production — versioning, registry, serving (MLflow)
• Build batch inference jobs that generate predictions at scale
• Integrate ML outputs with streaming infrastructure (Kafka) for downstream consumption
• Optimize SQL queries across multiple engines (Databricks SQL, PostgreSQL)
• Monitor data quality, pipeline reliability, and model serving health
• Collaborate with ML scientists to productionize their research

• 3+ years of professional Python development in a data or ML engineering context
• Strong PySpark experience — writing, debugging, and optimizing Spark jobs in production