Machine Learning Engineer

• Designing, building, and maintaining scalable data pipelines and ETL/ELT workflows supporting ML and GenAI use cases using Python, and AWS services.

• Building analytics tools that use the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.

• Managing data ingestion, orchestration, transformation, quality, and curation at scale.

• Implementing and maintaining systems via event-driven architectures and APIs.

• Collaborating closely with Data Scientists, product teams, and business stakeholders to translate data needs into robust solutions.

• Ensuring high engineering standards: unit testing, mocking, CI/CD, code quality, repository structure, environment setup.

• Providing technical guidance, code reviews, and mentoring to team members.

 

• Bachelor's degree in computer science, software engineering, or comparable work experience
• Proficiency in Python, including automation, scripting, and data engineering frameworks
•Experience in ML/GenAI projects 

• Strong experience with AWS, particularly: S3, Lambda, Step Functions, SQS/SNS, EventBridge, CloudWatch, IAM, DynamoDB, batch processing (Glue Jobs/Workflows, Batch). Other cloud providers are also welcomed
• Hands-on experience with Infrastructure as Code (preferably AWS CDK)
• Strong experience with Spark/PySpark or similar distributed processing frameworks
• Proficiency with Git, repo structure management, Docker, testing (unit tests, mocking, isolation)
• Practical knowledge of CI/CD pipelines (GitLab/GitHub Actions/CircleCI)
• Experience building scalable, production-grade data pipelines
• Great English skills, both written and spoken. 

 

• Experience with streaming systems (Kafka, Kinesis)
• Experience with dashboards or visualization tools (Quicksight, Streamlit, Dash)