Job Title

Job Title: AI/ML Lead – Generative AI & LLMs Location:Gurgaon Employment Type:Full-time Experience Level:6+YearsKey Responsibilities AI Model Development:Design, train, and fine-tune generative AI models, including LLMs and Retrieval-Augmented Generation (RAG) models, to solve real-world business problems. Prompt Engineering:Create, test, and optimize prompts to improve the relevance, coherence, and usefulness of model outputs. Cloud Deployment:Deploy and manage AI/ML solutions on cloud platforms such as AWS, Azure, or Google Cloud, ensuring performance, scalability, and cost-efficiency. Data Management:Partner with data scientists and data engineers to enable efficient data ingestion, preprocessing, and feature engineering pipelines. Model Evaluation & Optimization:Monitor model performance, run experiments, and iterate to enhance accuracy, latency, and resource efficiency. Innovation:Stay current with trends in AI, LLMs, generative models, and cloud infrastructure. Evaluate and integrate emerging tools and techniques. Cross-functional Collaboration:Work closely with product managers, software engineers, and business stakeholders to align AI initiatives with product goals. Documentation:Maintain thorough documentation of models, workflows, experiments, and deployment processes to ensure reproducibility and collaboration.Experience: Demonstrated experience developing and deploying AI/ML models, especially in Generative AI, LLMs, or RAG architectures. Hands-on experience working with one or more major cloud platforms (AWS, Azure, GCP). Experience with prompt engineering and optimization techniques for large language models.Technical Skills: Proficient in Python and AI/ML frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. Strong understanding of NLP techniques, machine learning algorithms, and data preprocessing pipelines. Experience with containerization and orchestration tools like Docker and Kubernetes is a plus. Familiarity with MLOps practices, CI/CD pipelines, and tools for automated model monitoring and deployment.