Ai Ml Engineer

Roles & Responsibilities

1. Strong proficiency in Python for data analysis, machine learning, and model development using libraries such as Pandas, NumPy, Scikit-learn, TensorFlow and PyTorch
2. Advanced SQL expertise for complex data extraction, transformation, aggregation, query optimization, and analytical processing across large-scale datasets.
3. Design, develop, and optimize Machine Learning models including classification, regression, clustering, anomaly detection, recommendation engines, and forecasting solutions.
4. Perform Exploratory Data Analysis (EDA), statistical modeling, feature engineering, and hypothesis testing to generate actionable insights and improve model performance.
5. Develop and maintain ETL/ELT frameworks for ingesting, transforming, validating, and processing structured and unstructured data from multiple enterprise data sources.
6. Build scalable data ingestion pipelines using BigQuery and GCP services, ensuring data quality, consistency, lineage, and availability for advanced analytics and machine learning workloads.
7. Implement data preprocessing and feature engineering pipelines to support model training, experimentation, and production-grade machine learning solutions.
8. Leverage Google Cloud Platform (GCP) technologies including BigQuery, Dataflow, Dataproc, Cloud Storage, and Cloud Composer (Airflow) for large-scale data processing and analytics.
9. Apply MLOps methodologies for model deployment, CI/CD automation, model monitoring, performance tracking, retraining strategies, and production support.
10. Collaborate with cross-functional teams including Data Engineering, Product, and Business stakeholders to translate business requirements into scalable AI/ML and analytics solutions.

Required Skills

• Strong expertise in Python
• Advanced proficiency in SQL
• Experience with Machine Learning, Deep Learning, and Statistical Modeling
• Hands-on experience with BigQuery and GCP
• Strong understanding of ETL/ELT Architecture, Data Pipelines, and Data Ingestion
• Experience with PySpark, Airflow, Dataflow, and Dataproc
• Knowledge of Data Warehousing, Data Modeling, and Database Management
• Experience implementing MLOps and Model Deployment Frameworks
• Strong analytical thinking and problem-solving skills

Experience : 6-7 years
Location : Hyderabad