Back
Mid-level GenAI role in Gurgaon with broad LLM/MLOps requirements increases candidate competition.
GenAI/NLP and MLOps skills are transferable but require domain-specific and cloud experience.
Explicit 4–9 years plus mandatory GenAI/NLP and cloud/MLOps skills makes shortlisting strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, deploy, and optimize Generative AI, NLP, and autonomous AI workflows across enterprise cloud platforms.
Lead AI model implementation and governance within CI/CD pipelines ensuring compliance with governance, risk, and security requirements.
Mentor and guide junior AI engineers; collaborate cross-functionally to translate business requirements into scalable AI solutions.
4–9 years experience in AI/ML/Data Science with at least 3 years specifically in Generative AI and NLP.
Proficiency in Python and hands-on experience with LLMs like OpenAI or AWS Bedrock, including experience deploying AI models on cloud platforms (AWS, Azure, or GCP).
Experience with Retrieval-Augmented Generation (RAG) pipelines, vector databases (e.g., Faiss, Pinecone), and MLOps concepts including version control (Git).
Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field.
Experienced in production deployment and governance of AI/ML solutions within regulated or compliance-focused environments.
Technical leader capable of mentoring engineers and driving AI architecture, deployment guidelines, and continuous operational improvements.
Hands-on practitioner comfortable working with cutting-edge GenAI/NLP technology stacks, cloud infrastructure, and responsible AI practices.