Job Summary

This role is responsible for architecting and designing enterprise-scale AI/ML solutions that leverage advanced machine learning frameworks and big data technologies. The individual will drive technical strategy, ensure alignment with business goals, and provide architectural leadership across multiple domains. They will establish governance, enforce best practices, and enable innovation by integrating cutting-edge tools and methodologies into solution delivery.

Key Responsibilities

1. Architect scalable AI/ML solutions using Python, TensorFlow, PyTorch, and Spark, ensuring alignment with business objectives and technical standards.
2. Design and implement robust data pipelines leveraging Apache Kafka, Spark, and Airflow to support real-time and batch processing for machine learning workflows.
3. Develop and optimize machine learning models using scikit-learn, XGBoost, and LightGBM, applying advanced techniques in NLP and time series forecasting.
4. Establish architectural governance by reviewing solution designs and enforcing compliance with industry best practices and organizational standards.
5. Integrate relational and distributed databases such as MySQL, PostgreSQL, and DataBricks to support scalable data storage and retrieval for AI/ML applications.
6. Lead cross-domain technical teams in the adoption and implementation of modern AI/ML frameworks, ensuring continuous knowledge upgradation and technology alignment.
7. Mentor and train team members in Python, ML model development, and big data technologies to build technical capability and reduce delivery risks.
8. Architect and implement RESTful API integrations to enable seamless communication between AI/ML components and external systems, ensuring scalable, secure, and efficient data exchange across diverse enterprise environments.
9. Architect and implement RESTful API integrations to enable seamless communication between AI/ML components and external systems, ensuring scalable, secure, and efficient data exchange across diverse enterprise environments.

Skill Requirements

1. Architectural Leadership In Ai/Ml, Demonstrating Strategic Technical Direction And Crossdomain Expertise.
2. Expert Proficiency In Python, Machine Learning Model Development, And Deep Learning Frameworks (Tensorflow, Pytorch).
3. Advanced Knowledge Of Big Data Processing Tools (Apache Spark, Kafka, Airflow) And Distributed Systems.
4. Solid Understanding Of Classical Ml, Nlp, Time Series Forecasting, And Data Engineering Principles.
5. Excellent Skills In Database Technologies Including Mysql, Postgresql, And Databricks.
6. Strong Command Of Data Science Libraries (Pandas, Numpy, Scikitlearn, Xgboost, Lightgbm, Spark Mllib).
7. Experience In Establishing Architectural Governance And Enforcing Compliance Measures.

Other Requirements

1. Recommended certifications: TensorFlow Developer Certificate
2. AWS Certified Machine Learning � Specialty
3. Databricks Certified Data Engineer Professional (optional but valuable)