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Protocol Intelligence
Data-driven signals on your job's competitivenessMetro Bangalore, mid-level ML role with broad MLOps and generalist requirements increases applicant competition.
Core ML/AI and MLOps skills transfer across industries, but client-hosted deployment experience raises domain specificity.
Explicit 4+ years plus mandatory Python, ML, MLOps, Kubernetes, and Azure requirements create stringent filters.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and deploy production-grade AI/ML systems with end-to-end ownership in client and internal environments.
Build and maintain scalable, modular Python AI/ML applications including API development and cloud-native deployment pipelines.
Own deployment, optimization, monitoring, troubleshooting, and incident management of AI systems in live enterprise and client-controlled infrastructure.
Minimum Requirements
4+ years of relevant experience in data science or AI engineering.
Strong proficiency in Python with experience in ML/DS libraries like Pandas, scikit-learn, PyTorch/TensorFlow, XGBoost/LightGBM.
Hands-on experience with CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes preferred).
Experience deploying AI/ML solutions on Microsoft Azure and working within client security and infrastructure constraints.
Ideal Candidate Profile
Experience building production AI systems with clear ownership from development to live operations in enterprise environments.
Strong Python engineering practices including testing, version control, and modular code design.
Familiarity with AI/ML deployment pipelines and client-facing or client-hosted ecosystem experience.