AI/Machine Learning Engineer with Databricks

We are looking for a hands-onAI/Machine Learning Engineer with proven experience deploying and running optimized feature engineering (offline and online), model training, and inference pipelines. Experience with unstructured data processing and Spark Streaming is a must. Real-time feature generation and inference are required for this project, along with batch pipelines for model training.

Responsibilities

• Design and optimize feature engineering pipelines for both batch and real-time workloads
• Build, deploy, and maintain scalable model training and inference pipelines
• Process structured and unstructured data at scale
• Develop streaming solutions using Spark Streaming
• Enable real-time feature generation and model serving
• Ensure reliability, scalability, and performance of ML solutions in production

Requirements

• 3+ years of experience building, deploying, and operating offline and online feature engineering pipelines
• Strong experience with model training and real-time inferencing pipelines
• Hands-on expertise in Databricks, Spark/PySpark, Python, and SQL
• Experience processing large-scale unstructured data
• Strong knowledge of Spark Streaming
• Experience with real-time feature generation and low-latency model inference
• Experience building and supporting batch pipelines for model training and retraining
• Proven track record of running production-grade ML systems
• English proficiency at B2 level or higher

Nice to have

• Experience with MLflow and MLOps
• Experience with AWS
• Background in Customer Analytics, Recommendation Systems, or Retail