Data Scientist

Job Description

We are looking for Data Scientist with GenAI solution & Python Development experience. Experience - 5+ Years Location - Bangalore Mandatory Skills - Data Science, Gen AI, Python, RAG. AI/ML, NLP, Azure, AWS. PFB JD Responsibilities: Implement and optimize AIML models and algorithms with a focus on Agentic AI and Retrieval Augmented Generation RAG Implement scalable machine learning models and algorithms to solve complex challenges Research and integrate the latest AI tools and frameworks into existing systems Stay uptodate with advancements in AIML research and apply them to practical problems Experiment with and implement Generative AI technologies across multiple domains Leverage cloud platforms like Google Cloud AWS and Azure for scalable AIML deployments Utilize opensource large language models LLMs such as LLama3 in AI application development Key Skills Strong understanding of Agentic AI concepts and applications Handson experience with RetrievalAugmented Generation RAG models Expertise in machine learning and deep learning frameworks eg TensorFlow PyTorch Experience with Large language models eg GPT4 LLama Azure OpenAI and integrating them into production systems Proficiency in programming languages such as Python and familiarity with libraries like Hugging Face Transformers langchain and llama index Experience in building and deploying AIML solutions using cloud platforms Azure Knowledge of data retrieval natural language processing NLP and reinforcement learning techniques Strong problemsolving skills and ability to work in a fastpaced collaborative environment Experience with model optimization finetuning and inference strategies to improve system performance Preferred Skills Experience with advanced NLP tasks like text generation summarization and question answering familiarity with reinforcement learning algorithms and their application in intelligent agent design Familiarity with containerization technologies eg Docker Kubernetes Background in computer vision and image generation techniques