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Mid-level ML role in Bangalore with broad ML/LLM/CV requirements increases applicant competition.
Core ML, deep learning and MLOps skills are broadly transferable across industries.
Explicit 3–10 year requirement plus mandatory ML, DL, LLM and MLOps tech stack.
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Lead development and deployment of classical machine learning and deep learning models targeting audience measurement and related problems.
Perform data preprocessing, feature engineering, exploratory data analysis, and rigorous model evaluation to optimize AI/ML solutions for production.
Collaborate with cross-functional teams and contribute to MLOps integration, model deployment, and mentoring of junior data scientists.
Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or related quantitative field.
3 to 10 years of hands-on experience developing and deploying AI/ML models, with strong focus on Computer Vision.
Proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or Keras.
Experience with Multi Modal Large Language Models (LLMs), transformer architectures, simple UI development for model interaction, and MLOps tools (e.g., Docker, Kubernetes, MLflow).
Experienced in both classical machine learning methods and deep learning, particularly in computer vision and multimodal LLM applications.
Strong software engineering skills with knowledge of deployment, version control, CI/CD, and collaboration within cross-functional teams.
Ability to lead AI/ML projects including mentoring, research, and innovation, with possible exposure to cloud AI/ML platforms and large-scale data processing.