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Metro Bangalore, mid-level AI role with broad LLM/MLOps requirements and popular experience band.
Core ML/LLM skills are transferable, but healthcare domain expertise and compliance needs increase sensitivity.
Multiple mandatory ML/LLM, MLOps, cloud, and infra skills plus explicit 6+ years requirement enforce strict shortlisting.
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Develop and maintain microservice architecture and API management solutions for AI/ML model integration and deployment.
Design and build scalable data pipelines and LLM inference architectures employing advanced optimization techniques for healthcare AI solutions.
Collaborate with cross-functional teams to research, optimize, and implement AI/ML and NLP solutions including prompt engineering, model fine-tuning, and A/B testing.
Bachelor’s degree in any Engineering Stream (Computer Science/Engineering preferred).
Minimum 6+ years of AI Engineering experience; preferred total experience is 8 years.
Proficiency in Python with data science and deep learning frameworks (PyTorch, TensorFlow), and experience with microservices and Kubernetes.
Experience with Infrastructure as Code (Terraform, CloudFormation), CI/CD pipelines, container orchestration, and LLM frameworks (Hugging Face Transformers, LangChain).
Experienced in end-to-end development of AI solutions with advanced skills in LLMs, including deployment and optimization in microservices architecture.
Strong domain expertise in ML/LLM lifecycle, feature engineering, and statistics applied to healthcare AI models.
Familiar with modern MLOps practices, cloud platforms, and collaborative cross-functional work environments involving data scientists and product managers.