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Tier-1 brand, broad ML requirements, metro location, and popular ML role increase competition.
Core ML engineering skills are transferable across industries, though domain experience increases fit sensitivity.
Explicit senior experience, mandatory ML stack, cloud and MLOps requirements enforce strict filtering.
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Design, develop, and deploy advanced AI and machine learning models with end-to-end ownership including data preprocessing, model deployment, and monitoring.
Collaborate closely with cross-functional teams to define and implement AI-driven solutions leveraging NLP, computer vision, predictive analytics, and scalable data pipelines.
Provide technical leadership and mentorship to junior team members while ensuring ethical AI practices, data privacy, and compliance.
3 to 5 years of work experience in AI/ML development.
Bachelor's degree in Engineering (BE/B.Tech) or Master's (M.Tech).
Strong proficiency in Python and AI/ML frameworks like TensorFlow, PyTorch, Scikit-learn.
Experience with cloud platforms (AWS, Azure, or GCP), SQL, and version control (Git).
Experienced in building scalable AI solutions with hands-on expertise in NLP, computer vision, or recommendation systems.
Familiar with deploying AI models using APIs, microservices, or MLOps tools and frameworks.
Able to lead AI projects with strong technical leadership and collaborative skills across diverse stakeholders.