Machine Learning and Deep Learning Architect

As an AI Technical Lead or Architect, your role involves collaborating with Business / Practice Units, Relevant Stakeholders and Customers to understand business goals and determine AI requirements. You will design and develop AI architectures, frameworks, and algorithms that can support large-scale and sophisticated AI solutions. Your key responsibilities include: Evaluating and selecting appropriate AI technologies, tools, and frameworks to achieve desired performance, accuracy, and scalability. Owning the development and implementation of AI models, ensuring consistency to standard processes in machine learning and deep learning. Developing and maintaining AI pipelines, incorporating data cleaning, pre-processing, feature engineering, model training, and validation processes. Conducting regular code reviews and providing technical guidance to junior members of the team. Staying up to date with the latest advancements in AI technologies, frameworks, and algorithms, and finding opportunities for their application in the organization. Collaborating with infrastructure teams to ensure smooth deployment and monitoring of AI models in production environments. In terms of qualifications and technical skills, you are expected to have a Bachelors or masters degree in computer science, Artificial Intelligence, or a related field. Experience working as an AI Technical Lead or Architect, along with working knowledge of machine learning, deep learning, and natural language processing (NLP) techniques is required. Proficiency in programming languages such as Python, Java, or C++, and familiarity with popular AI libraries and frameworks (e.g., TensorFlow, PyTorch, Keras) is important. You should also have experience in designing and implementing large-scale AI solutions, including data ingestion, storage, processing, and deployment. Good understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms is necessary. Excellent problem-solving and analytical skills, along with strong communication and teamwork skills are essential. Additionally, having the ability to stay updated with the latest advancements in AI technologies, frameworks, and platforms is crucial. Your technical skills should include proficiency in multiple machine learning (ML) and deep learning (DL) frameworks such as TensorFlow and PyTorch, along with expertise in programming languages like Python, R, SQL, Scala, and Julia. You should also have demonstrated proficiency in deploying Large Language Models (LLM) and Generative AI applications, with knowledge of techniques like Prompt Engineering Fine-Tuning (PEFT) and Retrieval-Augmented Generation (RAG). Experience in developing and deploying deep neural networks and ML models for intricate tasks is important. Moreover, hands-on experience in Service Oriented Architecture and the ability to lead solution development and delivery for the design solutions are required. It is beneficial to have knowledge of ethical considerations and responsible AI practices. Being able to share insights and expertise across the organization to foster thought leadership and innovative strategies for addressing various aspects of Responsible AI is an added advantage. As an AI Technical Lead or Architect, your role involves collaborating with Business / Practice Units, Relevant Stakeholders and Customers to understand business goals and determine AI requirements. You will design and develop AI architectures, frameworks, and algorithms that can support large-scale and sophisticated AI solutions. Your key responsibilities include: Evaluating and selecting appropriate AI technologies, tools, and frameworks to achieve desired performance, accuracy, and scalability. Owning the development and implementation of AI models, ensuring consistency to standard processes in machine learning and deep learning. Developing and maintaining AI pipelines, incorporating data cleaning, pre-processing, feature engineering, model training, and validation processes. Conducting regular code reviews and providing technical guidance to junior members of the team. Staying up to date with the latest advancements in AI technologies, frameworks, and algorithms, and finding opportunities for their application in the organization. Collaborating with infrastructure teams to ensure smooth deployment and monitoring of AI models in production environments. In terms of qualifications and technical skills, you are expected to have a Bachelors or masters degree in computer science, Artificial Intelligence, or a related field. Experience working as an AI Technical Lead or Architect, along with working knowledge of machine learning, deep learning, and natural language processing (NLP) techniques is required. Proficiency in programming languages such as Python, Java, or C++, and familiarity with popular AI libraries and frameworks (e.g., TensorFlow, PyTorch, Keras) is