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Tier-1 employer, mid-level ML role in Bangalore with broad AI/MLOps requirements drives high competition.
Core ML/MLOps skills are transferable, but healthcare/regulatory experience increases fit sensitivity moderately.
Explicit 3–6 years and mandatory ML/MLOps, cloud, and productionisation skills make filters moderately strict.
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Design, develop, and deploy production-grade AI solutions for MRI service lifecycle including predictive failure models, GenAI assistants, and contract analytics.
Build and maintain data pipelines and ML models, operationalizing them with best practices (MLOps/LLMOps, CI/CD) in a regulated healthcare environment.
Take prototypes to MVP and productization stage, monitor model performance, and optimize for key service outcomes like system uptime and resolution time.
Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
3-6 years of experience in Data Engineering, AI Engineering, Machine Learning Engineering, or related roles for Bachelor's degree holders; 4+ years if vocational qualification.
Experience working with AI/ML production pipelines and cloud AI platforms (Azure preferred) is strongly implied but not strictly mandatory.
Office-based role with onsite presence at least 3 days/week; must be comfortable working across global time zones (India, Europe, North America).
Experienced in deploying Generative AI and agentic AI applications in enterprise settings from POC to production.
Skilled in building scalable, compliant AI solutions in regulated environments, particularly healthcare or MedTech domains.
Able to collaborate cross-functionally with service engineers, data scientists, and product owners to translate real-world service problems into AI solutions.