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Known global brand, metro Bangalore location, and mid-level generalist ML role increase competition.
Specialized ML, computer vision and LLM experience required, but skills remain transferable across industries.
Explicit 3–10yr requirement plus mandatory CV, LLM and MLOps skills make filters strict.
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Lead design, development, training, and validation of classical machine learning models to solve business problems.
Perform extensive data preprocessing, feature engineering, exploratory data analysis, and model evaluation with rigorous optimization.
Collaborate with MLOps teams for production deployment and monitoring of ML models; mentor junior data scientists and document methodologies.
Bachelor’s, Master’s, or Ph.D. in Computer Science, AI, ML, or related quantitative field.
3 to 10 years of hands-on experience in developing and deploying AI/ML models, with a strong focus on Computer Vision.
Proficiency in Python and deep learning frameworks like PyTorch (preferred) or TensorFlow/Keras.
Experience with Multi Modal Large Language Models, MLOps tools (Docker, Kubernetes, Kubeflow, MLflow), and version control (Git).
Experienced in end-to-end ML model lifecycle including feature engineering, optimization, and production deployment within MLOps environments.
Strong background in both classical ML algorithms and deep learning architectures (CNNs, LSTMs, Transformers) with focus on Computer Vision use cases.
Capable of cross-functional collaboration with data teams and product stakeholders, and comfortable mentoring junior team members.