Machine Learning Engineer (Data Engineering Focus)

We are seeking a Machine Learning Engineer with a strong Data Engineering background to support enterprise-scale machine learning platforms. The ideal candidate will partner closely with Data Scientists to build and optimize production-ready ML data pipelines, feature engineering frameworks, and inference infrastructure., * Build and maintain production data ingestion pipelines for machine learning.

• Design and optimize feature engineering pipelines for large-scale ML workloads.
• Partner with Data Scientists to prepare production-ready datasets and reusable features.
• Support inference pipelines and production deployment.
• Integrate ML services into enterprise applications.
• Optimize feature pipelines for performance and scalability.
• Monitor production KPIs, data quality, and pipeline health.
• Maintain reproducible ML engineering workflows and version-controlled pipelines.

• 8+ years of software/data engineering experience
• Strong Python programming
• Spark / PySpark
• Databricks
• SQL
• Production Data Engineering
• Data Ingestion Pipelines
• Feature Engineering
• Feature Pipeline Development
• ML Inference Pipelines
• Model Deployment Support
• REST APIs / Microservices
• CI/CD for ML Pipelines
• Google Cloud Platform OR Azure or AWS Cloud
• Git, * Experience supporting enterprise ML platforms.
• Experience with MLOps tools.
• Financial Services or Banking experience preferred.

Candidates with recent experience primarily focused on Data Science, LLM/Generative AI, or end-to-end model development are not the target profile. The ideal candidate should have hands-on experience in production ML engineering with a strong focus on data ingestion, feature engineering, inference pipelines, and production deployment.