Generative AI

Job Title: Senior Machine Learning Engineer - Generative AI

Experience: 5-8 years

Location: Gurugram

Notice Period: Immediate to 30 days

Summary

As a Machine Learning Engineer, you will be a key member of the engineering team responsible for the advanced technical support, development, and deployment of machine learning models, with a special focus on Generative AI. You will be a critical contributor to the design and implementation of end-to-end software lifecycles for AI and machine learning products, ensuring high-quality and scalable solutions. This role requires a deep understanding of both machine learning principles and software engineering best practices, with a proven track record of bringing complex models from research to production, particularly within the Microsoft Azure ecosystem.

Responsibilities

• Lead the design, development, and deployment of production-level machine learning models, with a focus on generative AI models such as Large Language Models (LLMs), Generative Adversarial Networks (GANs), and Variational Autoencoders (VAEs).
• Provide advanced technical support for existing AI models, including bug fixes, addressing complex issues, and facilitating model expansion for new business cases.
• Act as a liaison between data scientists, cloud engineers, data engineers, and the business team to diagnose and resolve issues related to model performance and deployment.
• Lead the continuous improvement of support processes and workflows for ML applications.
• Develop, monitor, and maintain end-to-end machine learning pipelines (MLOps) including data preparation, feature engineering, model training, and deployment.
• Utilize Azure AI Foundry to build, test, and deploy cutting-edge AI-driven solutions and generative AI applications.
• Build model performance benchmarking, evaluation, and monitoring capabilities.
• Assess model performance to understand bugs, inefficiencies, and their root cause.
• Document and communicate best practices and troubleshooting procedures to support teams and stakeholders.
• Coordinate and mentor the Machine Learning Engineering team, promoting best practices and code quality.
• Stay current with the latest advancements in AI and machine learning technologies to provide informed support and recommendations.

Required Skills

• Minimum 4-7 years of experience in creating, deploying, monitoring, and maintaining machine learning models in cloud environments.
• At least 2-3 years of hands-on experience in developing and deploying Generative AI models.
• Strong experience working with advanced data analysis on large datasets.
• Hands-on experience with Azure for managing the end-to-end ML lifecycle.
• Proven experience with Azure AI Foundry for building and deploying AI-driven solutions.
• Familiarity with Snowflake and its AI/ML offerings.
• Experience in both front-end(UI/UX) and backend (API development, database management) technologies to build end-to-end solutions.
• Proficiency with data science and data engineering tools such as scikit-learn, XGBoost, pandas, NumPy, SciPy, and Jupyter notebooks.
• Strong understanding of software engineering tools and practices (Python, Git, CI/CD principles).
• Strong understanding of front-end technologies(like Javascript, React, Angular) and backend frameworks (eg Flask, Django)
• Experience with visual analytics platforms (e.g., Tableau, Streamlit).
• Database and other data storage technologies
• System infrastructure knowledge in Linux (Bash, Docker, CRON, Apache Airflow).
• Excellent problem-solving skills and attention to detail.
• Must be able to function independently as well as work in a collaborative team environment.
• Willingness to teach and learn new technologies.