AI ML Engineer

Data Analysis & Preparation: Independently collect, clean, pre process, and analyze structured and unstructured data to extract actionable insights and prepare datasets for model training and evaluation. Model Development: Design, develop, implement, and deploy machine learning models and algorithms to solve real-world business problems. Experimentation & Optimization: Design and conduct experiments, evaluate model performance using appropriate metrics, and optimize models for accuracy, scalability, and efficiency. Model Deployment & Maintenance: Collaborate on deploying ML models into production environments and monitor model performance over time. Documentation: Create and maintain clear documentation for data pipelines, experiments, models, and workflows to ensure reproducibility and knowledge sharing. Collaboration: Work closely with cross-functional teams including product, engineering, and data teams to integrate AI/ML solutions into existing systems and workflows. Mentorship & Review: Provide guidance to junior team members, participate in code reviews, and contribute to best practices within the team. Continuous Learning: Stay updated with the latest AI/ML research, tools, and industry trends, and proactively suggest improvements to existing solutions. Qualification: Educational Background: Bachelor?s or Master?s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field. Professional Experience: 2?4 years of hands-on experience in developing and deploying machine learning or data science solutions. Programming Skills: Strong proficiency in Python (or R) with experience in data manipulation and analysis using libraries such as Pandas, NumPy, and SciPy. Machine Learning Expertise: Solid understanding of machine learning algorithms including regression, classification, clustering, and model evaluation techniques. Data Handling: Experience working with large datasets, feature engineering, and data preprocessing pipelines. Analytical Skills: Strong problem-solving skills with attention to detail and the ability to translate business problems into ML solutions. Communication: Effective verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders. Team Collaboration: Proven ability to work in a collaborative, fast-paced environment and manage tasks independently. Preferred Qualifications: Frameworks & Tools: Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn. Deployment Experience: Exposure to model deployment using cloud platforms, APIs, or MLOps tools is a plus. Projects: Demonstrated experience through professional projects involving end-to-end ML solution development. Big Data & Databases: Familiarity with SQL, NoSQL databases, or big data tools is advantageous. Location: Chennai Experience: 2-4 years Mode of Work: Work from office