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Tier-1 brand, mid-level ML role in metro with broad skillset attracts many qualified applicants.
Highly domain-specific ML, cloud, and MLOps requirements limit cross-industry transferability.
Explicit 4–7 years plus mandatory ML and cloud skills create strict shortlisting filters.
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Develop and deploy scalable machine learning models and AI solutions using Python/PySpark and cloud platforms (AWS preferred, Azure acceptable).
Design ML pipelines and integrate ML models into enterprise applications with API development and containerization (Docker, Kubernetes).
Leverage ML frameworks and cloud AI services (SageMaker, Lambda, Step Functions) to optimize model performance and deployment.
4-7 years of relevant work experience in AI/ML development.
Bachelor of Technology (BTech) and/or Master of Business Administration (MBA) degrees required.
Proficiency in Python/PySpark and experience with ML frameworks such as scikit-learn, TensorFlow, PyTorch, and cloud platforms AWS or Azure.
Mandatory skills include Machine Learning and Azure/AWS platform expertise.
Experienced in building end-to-end machine learning solutions including model training, evaluation, deployment, and optimization.
Familiar with deep learning architectures (CNN, RNN, Transformers) and diverse AI use cases like NLP, computer vision, and recommendation systems.
Capable of designing scalable ML pipelines using cloud AI services and container orchestration tools ensuring secure and cost-effective deployments.