Generative AI Engineer - Tensorflow/PyTorch

Must have : Langchain, Microservices (Fast API) & Prompt engineering Skills : - AI engineer with Prompt engineering - Trying to build microservices using python, providing AI services - Best practices to build and maintain microservices - Use FastAPI to interface microservices, using GPT4 - SE that has building microservices, closely building chatbot, aware of ChatBot - Focusing on Langchain, focusing on vector databases based on Azure services Framework : Python, Langchain,Chroma DB, Azure AI services Nice to have : Langgraph Key Responsibilities : - Model Development : Develop and fine-tune generative models, such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and transformers, to solve business problems. - Collaboration : Work closely with data scientists, engineers, product teams, and business stakeholders to identify opportunities for AI integration and translate those into actionable technical plans. - Data Handling : Collect, preprocess, and manipulate large datasets for model training and testing. Ensure data quality and integrity. - Innovation : Stay updated on the latest trends, research papers, and advancements in generative AI technologies, bringing fresh ideas to the team. - Deployment : Deploy AI models into production environments, ensuring scalability, performance, and integration with existing systems. - Optimization : Continuously improve models for performance, efficiency, and cost-effectiveness. - Documentation : Maintain thorough documentation on models, methodologies, and processes for internal knowledge sharing and future model iterations. - Compliance & Ethics : Ensure all AI developments adhere to ethical guidelines and privacy regulations. Required Skills & Qualifications : - Education : Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related field. - Experience : 3 years of experience in AI/ML model development with a strong focus on generative models. Skills : - Expertise in deep learning frameworks like TensorFlow, PyTorch, or similar. - Strong understanding of GANs, VAEs, transformers, and other generative algorithms. - Proficiency in programming languages such as Python, with experience in libraries like NumPy, pandas, and scikit-learn. - Familiarity with cloud platforms (e.g., AWS, GCP, Azure) for model deployment. - Knowledge of NLP techniques and large language models (e.g., GPT, BERT) is a plus. - Experience with version control (Git) and agile methodologies. - Strong problem-solving skills and ability to work in a fast-paced environment. (ref:hirist.tech)

Location: in, IN

Posted Date: 4/4/2025