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Mid-level generalist ML title, 3–6 year band, and Bengaluru metro increase candidate competition.
Specialized ML, computer-vision and LLM requirements make background transferability across industries limited.
Explicit 3–10 years plus mandatory ML/CV/LLM, deep learning and MLOps skills create strict filters.
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Lead design, development, training, validation, and deployment of classical machine learning and deep learning models for audience measurement and business problem-solving.
Perform extensive data preprocessing, feature engineering, exploratory data analysis, and model optimization to deliver impactful AI/ML solutions.
Collaborate with cross-functional teams including MLOps/DevOps to integrate and maintain models in production, while mentoring junior data scientists and driving research innovation.
Bachelor's, Master's or Ph.D. in Computer Science, AI, Machine Learning, or related quantitative fields.
3 to 10 years hands-on experience developing and deploying AI/ML models, with a strong focus on Computer Vision.
Proficiency in Python and deep learning frameworks (PyTorch preferred, or TensorFlow/Keras).
Experience with Multi-Modal Large Language Models, MLOps tools (Docker, Kubernetes, Kubeflow, MLflow), and full stack development in at least one stack.
Experienced in both classical machine learning and cutting-edge deep learning techniques, including transformer-based LLMs and multi-modal AI.
Skilled in end-to-end AI/ML lifecycle including model development, evaluation, optimization, deployment, and monitoring with strong software engineering and MLOps practices.
Able to collaborate across technical and business teams to deliver production-grade models and mentor less experienced colleagues in a dynamic environment.