Back
Senior, specialized ML role in Bangalore at a non-Tier-1 company reduces applicant density.
Highly specialized ML/AI and LLM-focused skills limit cross-industry transferability.
Explicit 9–14 years plus strong mandatory ML/LLM, deployment, and engineering requirements make filters strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design and development of advanced AI/ML models using various data types to enhance Omnissa's AI platform capabilities.
Collaborate with engineering and product teams to build, deploy, and operationalize scalable ML pipelines and solutions in cloud environments.
Drive best practices in ML engineering, model evaluation, experimentation, and responsible AI governance, focusing on Large Language Models, RAG, and AI Agents.
9 to 14 years of experience in data science, machine learning engineering, or applied AI roles.
Proficiency in Python and working knowledge of at least one other programming language such as Java or C++.
Hands-on experience with advanced AI/ML frameworks including Scikit-learn, NumPy, Pandas, and Hugging Face Transformers.
Experience working with Large Language Models (LLMs), prompt engineering, vector databases for RAG, orchestration frameworks (LangChain, LangGraph), and deployment of ML models on cloud platforms (AWS, Azure, or Google Cloud).
Experienced in managing end-to-end ML lifecycle in production-scale cloud environments with strong software engineering skills including CI/CD and observability.
Deep expertise in NLP, LLMs, and Retrieval Augmented Generation systems with practical experience deploying AI agents and multi-agent systems.
Capable of leading cross-functional collaboration to integrate AI/ML solutions into complex product ecosystems, focusing on scalability, performance, and cost optimization.