Senior Analyst - AI/ML

**What you'll do:** Senior Analyst AI/ML Engineer ________________________________________ Role Overview We are looking for a motivated AI/ML Engineering graduate to join our Artificial Intelligence and Machine Learning (AIML) team. This role is ideal for a 4-5 year experienced candidate with a strong academic foundation in AI/ML who is eager to apply theory to real world business problems under mentorship. You will work closely with senior AI/ML engineers, data scientists, and platform teams to build, experiment with, and operationalize machine learning solutions on enterprise scale data platforms. ________________________________________ Key Responsibilities - Assist in building and training machine learning models for structured and unstructured data use cases - Perform data analysis, preprocessing, and feature engineering on large datasets - Support experimentation using AutoML and custom ML approaches - Evaluate model performance and assist in tuning for accuracy and robustness - Work with AI/ML platforms and tools for model development and experimentation - Collaborate with engineers and analysts to understand business problems and translate them into ML tasks - Document experiments, learnings, and model outcomes clearly - Follow best practices for responsible AI, data governance, and security **Qualifications:** - Bachelor's degree in Engineering (B.E./B.Tech), 4 to 7 years of work experience. **Skills:** o Artificial Intelligence o Machine Learning o Data Science o Computer Science (with strong AI/ML coursework) - Strong fundamentals in: o Machine Learning algorithms o Statistics and linear algebra o Data structures and basic algorithms - Working knowledge of Python - Familiarity with ML libraries such as: o scikit learn o TensorFlow or PyTorch (basic exposure is sufficient) - Basic understanding of SQL and working with datasets ________________________________________ Good to Have - Exposure to: o Cloud platforms (Azure / AWS / GCP) o Data platforms like Snowflake o ML lifecycle concepts (training, evaluation, deployment) - Academic or personal projects involving: o Predictive modeling o NLP or computer vision o Time series forecasting - Familiarity with notebooks, Git, or basic MLOps concepts