Data Scientist - Artificial Intelligence/Machine Learning

Job Description : As a Data Scientist, you will identify business trends and solve complex problems using large-scale data and advanced AI techniques. You will design, develop, and deploy high-impact solutions ranging from classical ML/DL to LLM-powered applications including RAG-based architectures and Agentic AI systems.Key Responsibilities :- Analyze existing digital products to understand current intelligent models and improve their performance, reliability, and scalability.- Enhance traditional ML and DL pipelines by incorporating LLM-based capabilities such as summarization, Q&A, reasoning, decision support, and copilots.- Design and implement LLM-based solutions using Retrieval-Augmented Generation (RAG) to ground responses on enterprise data.- Build Agentic AI workflows that enable multi-step task planning, tool and API invocation, and contextual memory management.- Develop agent orchestration patterns such as multi-agent collaboration, deterministic workflow engines, and fallback mechanisms.- Drive innovation through experimentation and contribute to invention disclosures and patents.- Design and implement AI solutions for IoT, robotics, and automation use cases.- Build and maintain scalable pipelines for model training, evaluation, and deployment.- Manage experiment tracking, model versioning, and model registries.- Define and track LLM-specific evaluation metrics including groundedness, faithfulness, hallucination rate, and safety.- Monitor retrieval system quality using metrics such as precision, recall, and latency.Required Qualifications :- Masters degree in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, or a related field (PhD preferred).- Strong oral and written communication skills.- Demonstrated ability to take ambiguous objectives and design innovative, flexible solutions.- Proven track record of delivering impactful outcomes.Technical Skills :- Expertise in Large Language Models (LLMs) and building production-grade applications.- Hands-on experience with RAG architectures, embeddings, vector search, and reranking mechanisms.- Experience building tool-using agents and multi-step agent workflows.- Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate, Elasticsearch).- Experience with agent frameworks (e.g., LangChain, Semantic Kernel, LlamaIndex).- Experience with LLMOps tooling: prompt management, evaluation harnesses, and observability.- Cloud experience (Azure/AWS/GCP), containerization (Docker), and Kubernetes.Behavioral Competencies :- Strong ownership mindset and proactive leadership.- Collaborative team player with an innovation-first approach. (ref:hirist.tech)