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Tier-1 brand, Bangalore location, mid-level generalist ML/LLM role with broad MLOps requirements creates high competition.
Specialized ML, MLOps, and LLM expertise is transferable across industries but favors experienced ML backgrounds.
Explicit seven-year requirement plus mandatory MLOps, LLM, cloud, and specific tech stacks increases shortlisting strictness.
Develop and deploy traditional machine learning models and large language models, ensuring robust data processing and pipeline development.
Lead design and optimization of AI/ML features focusing on scalability, performance, and cloud cost efficiency (preferably on AWS).
Collaborate across multiple teams including architecture, product lifecycle, security, and release management through Agile methodologies.
Minimum 7 years full-time professional experience in Machine Learning and MLOps.
Strong programming skills in Python and familiarity with Python ML libraries (Pandas, PyTorch, TensorFlow, Spark).
Experience with data engineering tools such as Apache AirFlow, PySpark and ML platforms like MLFlow.
Location requirement: Based in Bangalore, Karnataka, India.
Experienced practitioner with deep knowledge of ML lifecycle including model training, tuning, validation, and deployment.
Proficient in cloud AI services (notably AWS SageMaker and Bedrock) and big data architectures including Data Lakehouse.
Skilled in building scalable AI applications involving vector databases, conversational AI, and container orchestration within an Agile environment.