Software Engineer Generative AI

Overview

Company:IT Services Organization

Key Skills: Machine Learning, SQL, Python, ETL, Hive

Roles and Responsibilities:

1. Generative AI Model Development

• Design, develop, and deploy Generative AI solutions using advanced Machine Learning techniques.
• Fine-tune and optimize Large Language Models (LLMs) for enterprise use cases.
• Implement prompt engineering strategies and Retrieval-Augmented Generation (RAG) pipelines.

2. Machine Learning Engineering

• Build, train, evaluate, and deploy ML models using Python-based frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Perform feature engineering, model validation, and hyperparameter tuning.
• Ensure scalability, reliability, and performance of ML models in production.

3. Data Engineering & ETL

• Develop and maintain ETL pipelines using Python and SQL to support AI/ML workflows.
• Work with structured and unstructured datasets for model training and inference.
• Utilize Hive and distributed data processing frameworks for large-scale data environments.

4. Database & Query Optimization

• Write optimized SQL queries for data extraction, transformation, and analysis.
• Design and maintain data schemas supporting AI and ML applications.
• Ensure data integrity, security, and performance across databases and warehouses.

5. Model Deployment & MLOps

• Deploy AI/ML models using APIs and microservices architecture.
• Implement monitoring, logging, and performance tracking for production systems.
• Support CI/CD pipelines and automate model lifecycle management.

6. Performance & Scalability

• Optimize Python code and ML workflows for efficiency and scalability.
• Leverage distributed computing frameworks for large-scale processing.
• Conduct stress testing and capacity planning for AI applications.

7. Collaboration & Documentation

• Collaborate with data scientists, engineers, product teams, and business stakeholders.
• Document model architectures, ETL processes, and deployment workflows.
• Provide technical mentorship and guidance for AI initiatives.

8. Governance & Responsible AI

• Ensure data privacy, governance, and ethical AI practices.
• Implement bias detection, validation, and monitoring mechanisms.
• Maintain compliance with security and regulatory standards.

Skills Required:

• Strong experience in Machine Learning and Generative AI solutions.
• Advanced proficiency in Python for ML and data engineering tasks.
• Expertise in SQL and database optimization techniques.
• Experience with ETL processes and large-scale data environments.
• Knowledge of distributed data tools such as Hive.
• Experience in deploying models using APIs and microservices.
• Understanding of MLOps, CI/CD, and cloud environments (preferred).
• Strong analytical, architectural, and problem-solving skills.

Education: Any Graduation (Bachelor's degree in Computer Science, Data Science, or related field preferred).