As a AI Specialist, you will be responsible for developing cutting-edge deep learning models and algorithms to advance the field of generative artificial intelligence. Your expertise will contribute to solving complex problems and creating novel solutions in areas such as image synthesis, natural language processing, and data generation. The ideal candidate will possess a strong background in deep learning, excellent problem-solving skills, and a passion for pushing the boundaries of AI research.

As part of your duties, you will be responsible for:

• Develop and implement state-of-the-art generative AI models and algorithms.
• Conduct research and experimentation to improve existing models and propose novel approaches.
• Collaborate with cross-functional teams to integrate generative AI solutions into real-world applications.
• Stay up-to-date with the latest advancements in deep learning and generative models and apply them to enhance our AI capabilities.
• Document research findings, prepare technical reports, and contribute to whitepaper/scientific publications.
• Provide deep leadership and coaching in the project delivery lifecycle. Focus on shared learning, continuous improvement, and drive adoption of best practices.

Qualifications and experience we consider to be essential for the role:
• Track record in relevant research, such as deep learning and deep generative models, as evidenced by publications in top-tier venues (e.g., ICML, NeurIPS, ICLR, UAI, AIStats).
• Hands-on experience with current deep learning frameworks (e.g., PyTorch, TensorFlow) as evidenced by released code (e.g., GitHub repositories – version control awareness).
• Solid understanding of optimization techniques for training deep neural networks, regularization methods, and hyperparameter/fine tuning.
• Experience in Generative AI Models (Text to Text, Text to Image), finetuning, prompt engineering and experience with frameworks like Langchain
• Strong software engineering skills for rapid and accurate development of AI models and systems.
• Provide business-oriented solution with ability to communicate effectively, both verbally and in writing, with technical and non-technical stakeholders.
• Experience working in a collaborative environment, contributing to multidisciplinary teams and projects.
• Proven ability to solve complex problems, think creatively, and adapt to evolving research trends.

Skills and Personal attributes we would like to have:
• Strong educational background with a completed (or on-track to complete) PhD in deep learning, machine learning, related area, or equivalent experience.
• Foundational mathematical concepts such as linear algebra, calculus, and probability theory, which are essential for understanding and developing deep learning models.
• Solid knowledge of deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer models.
• Familiarity with key concepts and techniques used in generative models, such as variational autoencoders (VAEs), generative adversarial networks (GANs), and flow-based models.
• Strong programming skills in languages such as Python, along with experience working with popular deep learning frameworks like PyTorch and TensorFlow.
• Knowledge of MLOps deployment and hosting.
• Experience with large-scale data processing and distributed computing frameworks (e.g., Apache Spark, TensorFlow distributed).
• Understanding of Graph Database and Vector Database along with knowledge of cloud computing platforms (e.g., AWS, Google Cloud).
• Experience with deploying AI models in production environments.
• Proficiency in additional programming languages, such as C++, Java, or R.
• Familiarity with domain-specific applications of generative AI, such as computer vision, natural language processing, or healthcare.