CareerPlanGet AI match score →

Ai Ml Engineer

💼 Full-time🗓 2026-07-31

Core

Design and manage full data pipelines for AI accuracy, personalization, and business KPIs.

Role type

Data Scientist (Data Engineering focus)

Builds

End-to-end data pipelines, ETL/ELT automation, and data features for ML models

Domain

AI/ML, Data Engineering, Cloud (Azure)

Deliverable

production ML models

Required skills

Python (advanced), SQL, Pandas, NumPy, Azure Data Factory, Cosmos DB, Blob Storage, ETL/ELT pipeline design, feature engineering, statistical modeling, data drift monitoring, GDPR compliance

Preferred skills

PySpark, Databricks, streaming data, ML competitions

Technologies

Azure Data Factory, Cosmos DB, Blob Storage, MLflow, Airflow, Azure ML, Python, PowerBI, Matplotlib, Plotly

Responsibilities

Develop and manage end-to-end data pipelines; Collect, mine, and clean multi-modal data; Build and launch experiments including feature engineering and statistical modeling; Automate ETL processes and monitor data quality; Collaborate with ML/NLP teams to productionize data features; Visualize results using Python or PowerBI

Seniority

Mid-Senior, hands-on IC

Rewrite
## About the role As a Data Scientist at EVEOAI, you will design and manage the full data pipeline—from collection and preprocessing to analysis, model feature creation, and ETL automation. Your insights will directly impact AI accuracy, personalization, and business KPIs. ## Core Responsibilities - Develop and manage end-to-end data pipelines using Azure Data Factory, Blob Storage, and Cosmos DB. - Collect, mine, and clean multi-modal data (images, text, user logs) for data-driven insights and model training. - Build and launch experiments: feature engineering, EDA, statistical modeling, and dashboard reporting. - Automate ETL processes; monitor and handle data drift, quality, and compliance (GDPR). - Collaborate with ML/NLP teams to productionize data features and monitor real-time pipelines. - Visualize results with Python (Matplotlib, Plotly), PowerBI, or similar tools. ## Requirements - BTech/MSc/PhD (or equivalent) in Computer Science, Data Science, or related quantitative field. - Strong Python skills; advanced with Pandas, NumPy, SQL. - Experience with Azure data ecosystem: Data Factory, Cosmos DB, Blob Storage. - Proficient in building, scaling, and maintaining ETL/ELT pipelines. - Knowledge of model deployment and monitoring (MLflow, Airflow, Azure ML). - Bonus: Advanced experience in big data (PySpark, Databricks), streaming, or industry-leading ML competitions.
Sourced via wellfound · Listed on CareerPlan, which tracks 70,000+ jobs from 20+ sources.
Apply on Wellfound ↗