AI/Machine Learning Engineer with Databricks
We are looking for a hands-on AI/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
