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Mid-level GenAI role in Gurugram with common ML and infra requirements yields medium competition.
LLM development, vector search, and MLOps skills are broadly transferable across industries.
Explicit 5–8 years plus mandatory LLM, vector DB, cloud, and deployment skills makes shortlisting highly strict.
Lead design, development, and deployment of scalable Generative AI and AI/ML models focused on automation, intelligence, and creativity.
Oversee full AI model lifecycle: data collection, preprocessing, training, fine-tuning, deployment, and monitoring.
Mentor junior engineers, drive AI initiatives from concept to production, and maintain production-ready AI systems including pipelines and APIs.
5-8 years of experience in AI/ML model development and deployment.
Bachelor's or Master's degree in Computer Science, AI, ML, Data Science, or related field.
Proficient in Generative AI, Large Language Models (LLMs), Python, and AI frameworks (PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex).
Experience with vector databases (Pinecone, Weaviate, ChromaDB, FAISS), cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes), and MLOps practices.
Senior-level AI engineer with deep domain expertise in Generative AI, LLMs, NLP, and multimodal AI.
Experienced in deploying scalable, high-performance AI systems with strong technical leadership and mentoring skills.
Comfortable working cross-functionally to integrate AI solutions into products and workflows with knowledge of AI infrastructure and emerging AI research.