Machine Learning / Data Science Engineer

Project:
End-to-end delivery of ML solutions, from data processing, through model development and deployment, to operations and monitoring. The candidate will participate in model design and development, system integration (API/batch), setting up CI/CD pipelines, and implementing monitoring.

Responsibilities:
● Develop and deploy ML models into production (API/batch)
● Build CI/CD pipelines, containerization, and cloud operations
● Work with the data stack (DB/DWH, data lakes, ETL/ELT orchestration)
● Monitor models, testing, and ensuring data quality
● Collaborate with stakeholders, conduct product analytics and A/B tests
● Documentation, success metrics, and solution iteration

Technologies / Requirements:

Must-have
● 3+ years of experience with Python and SQL in a production environment
● Model deployment into production (API/batch) and operations
● CI/CD pipelines, Docker, cloud (AWS/Azure/GCP)
● Orchestration (Airflow/Prefect) and experiment tracking (MLflow/W&B)
● Testing (unit/integration) and monitoring of both models and data

Nice-to-have
● Kubernetes, Spark, Kafka, dbt, Great Expectations, Feature Store (Feast)

● Basic frontend for internal tools (Streamlit/Next.js)

● Experience with A/B testing and product analytics

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