Job Summary

This role is responsible for providing architectural leadership in the design and implementation of advanced AI/ML solutions, ensuring scalability, reliability, and alignment with organizational strategy. The position drives innovation by leveraging deep expertise in machine learning, big data platforms, and cloud technologies to deliver enterprise-grade solutions that meet evolving business needs and industry standards.

Key Responsibilities

1. Architect and design scalable AI/ML solutions using Python, TensorFlow, PyTorch, and Spark, ensuring alignment with business requirements and technical best practices.
2. Lead the development and integration of machine learning models leveraging scikit-learn, XGBoost, and Spark MLlib, optimizing for performance and accuracy across large datasets.
3. Define data pipelines and orchestration workflows utilizing Apache Airflow, Kafka, and Databricks to enable robust, real-time analytics and model deployment.
4. Establish and enforce architectural governance and compliance measures, reviewing design deliverables to ensure adherence to industry standards and organizational policies.
5. Guide the team in implementing data storage and retrieval solutions using MySQL, PostgreSQL, and cloud-based platforms, ensuring data integrity and scalability.
6. Mentor and develop team members in advanced AI/ML concepts, fostering technical growth and mitigating delivery risks through ongoing training and knowledge sharing.
7. Contribute to thought leadership by submitting whitepapers, participating in industry forums, and supporting patent filings to advance the organization’s technical reputation.
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.

Skill Requirements

1. Architectural Leadership In Ai/Ml, Demonstrating Expert Proficiency In Designing Enterprisescale Machine Learning Solutions.
2. Excellent Knowledge Of Python, Machine Learning Model Development, And Big Data Frameworks Such As Apache Spark.
3. Expertlevel Experience With Tensorflow, Pytorch, Scikitlearn, And Advanced Ml Algorithms Including Deep Learning, Nlp, And Time Series Forecasting.
4. Advanced Proficiency In Data Engineering Tools Including Apache Kafka, Airflow, And Databricks.
5. Solid Understanding Of Relational Databases (Mysql, Postgresql) And Cloud Data Platforms.
6. Excellent Ability To Drive Innovation, Enforce Governance, And Align Technology Solutions With Strategic Business Objectives.

Other Requirements

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