AI / ML Engineer

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Data Science, Machine Learning (ML), Python Frameworks, MySQL Good to have skills : NA Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education

Summary:

We are looking for a skilled Data Scientist with strong experience in traditional machine learning techniques such as regression, classification, and statistical modeling. The ideal candidate should have deep expertise in Python and SQL, strong analytical thinking, and hands-on experience in building and validating predictive models. This role is not focused on GenAI/NLP, and candidates with heavy LLM-focused profiles without strong core Data Science fundamentals may not be suitable.

Roles & Responsibilities:

• Expected to be an SME, collaborate and manage the team to perform.
• Responsible for team decisions.
• Engage with multiple teams and contribute on key decisions.
• Provide solutions to problems for their immediate team and across multiple teams.
• Lead the design and implementation of AI-driven solutions ensuring alignment with business objectives.
• Facilitate knowledge sharing and mentoring within the team to foster professional growth.
• Coordinate with stakeholders to gather requirements and translate them into technical specifications.
• Monitor project progress and implement improvements to optimize workflows and deliverables.

• Develop, train, and deploy machine learning models for classification, regression, and predictive analytics use cases
• Perform data exploration, preprocessing, and feature engineering on large and complex datasets
• Apply statistical techniques (hypothesis testing, distributions, variance analysis) to derive meaningful insights
• Design and execute robust model validation frameworks (cross-validation, A/B testing, performance tuning)
• Conduct hyperparameter tuning to improve model accuracy and efficiency
• Write optimized and scalable SQL queries for data extraction, transformation, and analysis