Machine Learning Engineer

Design, build and maintain scalable data pipelines for integrating diverse data sources.

Implement and manage scalable data architectures and infrastructure to support analytics

Collaborate with data scientists, ML engineers, and product teams to enable seamless data flow for AI/LLM-driven use-cases.

Develop and optimize ETL processes for continuous data ingestion and transformation.

Ensure data quality, integrity, and security, including anonymization and access controls.

Support the development of interactive dashboards and query-assist tools for business users.

Contribute to the feedback loop for continuous improvement of data-driven insights.

Deploy and monitor pipelines on AWS cloud and/or edge infrastructure.

You are a successful candidate if you have:

strong experience with data engineering tools and frameworks (e.g., Python, SQL, Spark, Airflow).

hands-on experience with cloud data platforms (AWS, Azure, or GCP).

familiarity with federated data architectures and large-scale data integration.

experience working with both structured and unstructured data.

knowledge of data privacy, security best practices, and compliance (anonymization, access control, audits).

the ability to work in cross-functional teams (data scientists, ML engineers, product managers).

experience in automotive, marketing analytics, or customer intelligence domains is a plus.

exposure to Al/LLM-based systems

experience with dashboarding tools (Power BI, Tableau, or similar).

familiarity with DevOps/SecOps practices for data infrastructure