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Tier-1 brand, Bangalore metro, mid-level ML generalist with broad cloud/GenAI skillset increases candidate competition.
Core ML, cloud and MLOps skills are highly transferable across industries, lowering background sensitivity.
Explicit 3–8 years requirement and many mandatory ML, cloud, and MLOps skills impose strict filters.
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Design, build, and deploy AI/ML models for use cases including classification, regression, NLP, and computer vision.
Collaborate with data engineers to develop data pipelines and integrate AI/ML models into production environments, leveraging cloud platforms (Azure/AWS/GCP) and MLOps.
Engage with clients and manage project delivery in AI/ML, contribute to reusable assets and build internal capabilities.
3+ years of AI/ML engineering experience with cloud environment exposure.
Proficiency in Python, PyTorch/TensorFlow, and GenAI/Agentic frameworks.
Experience with cloud-native AI services (Azure ML, AWS SageMaker, GCP Vertex AI).
Educational qualifications: BE, B.Tech, ME, M.Tech, MBA, or MCA with 60%+ marks.
Demonstrated experience deploying AI/ML solutions in enterprise or client-facing environments.
Familiarity with advanced AI concepts like vector databases, RAG pipelines, autonomous agents, and multi-agent systems.
Ability to manage stakeholder communication and work across geographies in collaborative project settings.