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About the role
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
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