Senior AI/ML Developer with RAG Experience

Job Description

Position Overview: We are looking for a passionate and experienced AIML Engineer with a strong background in Python, AI/ML, and Generative AI technologies. The ideal candidate will be responsible engaging team of talented engineers, overseeing the development and implementation of AI/ML models, and ensuring the delivery of high-quality, scalable solutions. Key Responsibilities: Design, develop, and deploy AI/ML/GenAI models and algorithms using Python and relevant frameworks. Drive the development of Generative AI solutions, including natural language processing (NLP), Embedding models, Text retrieval Reinforcement Learning, and other related technologies. Deploying LLM's in Container like TGI, VLLM, TensorRT or similar frameworks. Collaborate with cross-functional teams to define project requirements, scope, and timelines. Ensure the scalability, performance, and reliability of AI/ML solutions. Stay updated with the latest advancements in AI/ML and GenAI technologies and incorporate them into projects. Provide technical guidance, and ensure best practices in software development. Communicate effectively with stakeholders, presenting technical concepts and project progress. Qualifications: Bachelor's or masters degree in computer science, Engineering, or a related field. Proven experience as a AIML Engineer with production grade projects. Strong proficiency in Python and experience with AI/ML frameworks such as TensorFlow, PyTorch, and scikit-learn. Hands-on experience with Generative AI technologies, including NLP, computer vision, and deep learning. Solid understanding of data structures, algorithms, and software design principles. Experience with cloud platforms (e.g., AWS) and containerization technologies (e.g., Docker, Kubernetes). Excellent problem-solving skills and the ability to think critically and analytically. Strong communication and interpersonal skills, with the ability to work effectively in a team-oriented environment. Preferred Qualifications: Knowledge of RAG, RAGAS Evaluation frameworks is a big Plus. Knowledge of reinforcement learning and other advanced AI techniques. Contributions to open-source AI/ML projects or publications in relevant conferences/journals.