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Popular mid-level ML/AI role in Bengaluru with broad LLM/CV/MLOps requirements increases candidate competition.
Core ML, LLM and MLOps skills are transferable, though CV/media expertise raises domain specificity.
Explicit 3–10 years plus required deep learning, LLM and MLOps skills will tightly filter applicants.
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Lead the design, development, training, validation, and deployment of classical machine learning models and neural network architectures for audience measurement and computer vision applications.
Perform extensive data preprocessing, feature engineering, exploratory data analysis, and model optimization including hyperparameter tuning and cross-validation to improve model performance.
Collaborate with cross-functional teams including MLOps/DevOps to deploy and monitor ML models in production and mentor junior data scientists on best practices and innovation.
Bachelor's, Master's, or Ph.D. in Computer Science, AI, Machine Learning, or related quantitative field.
3 to 10 years of hands-on experience in AI/ML model development and deployment, with a strong focus on computer vision.
Proficient in Python (including Scikit-learn, Pandas, NumPy) and deep learning frameworks PyTorch (preferred), TensorFlow, Keras.
Experience with Multi Modal Large Language Models (LLMs), MLOps tools and principles, and full stack development in at least one stack.
Experienced in developing and deploying AI/ML solutions in production environments with an emphasis on classical and deep learning models relevant to audience behavior and computer vision.
Skilled in bridging technical requirements with business objectives through collaboration with cross-functional teams and effectively mentoring others.
Demonstrates strong software engineering discipline including version control, testing, CI/CD, and building simple UIs for model interaction or data annotation.