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Tier-1 brand, mid-level role, metro location present, but niche ML/LLM skills limit broad applicant pool.
Skills transferable across industries, but LLM and enterprise consulting needs increase domain specificity.
Explicit 3–5 years and many mandatory ML, deployment, and MLOps skills make screening stringent.
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Design, develop, and deploy AI/ML models and end-to-end AI pipelines including data ingestion, processing, model validation, and production deployment.
Implement and optimize LLM-based solutions, NLP workflows, chatbots, and generative AI applications within business contexts.
Collaborate with business and cross-functional teams to define AI solution architectures, integrate models via APIs or cloud services, and ensure data pipeline stability.
3–5 years of experience in AI/ML development including practical model deployment.
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related fields.
Strong programming skills in Python with experience using NumPy, Pandas, Scikit-Learn, TensorFlow or PyTorch, and Hugging Face Transformers.
Experience deploying AI models using cloud platforms like Azure ML, AWS SageMaker, or GCP Vertex AI.
Experienced in building scalable AI solutions, particularly in NLP, computer vision, or generative AI projects with practical deployment expertise.
Familiar with MLOps practices, CI/CD, model monitoring, and AI integration using APIs or microservices in cloud environments.
Ability to translate complex AI/ML concepts into business value and work effectively in client-facing and consulting scenarios.