Key Responsibilities - Member of the in-house AI Center-of-Excellence team that works on challenging problems in advanced AI (including areas on generative multimodal AI, autonomous agent, NLP, computer vision, recommender system), mathematical optimization, game theory, and experimental design. - Research and develop advanced machine learning algorithms to meet complex product requirements. The scope includes defining hypotheses, executing necessary tests and experiments; evaluating, tuning and optimizing algorithms and methods; and having an eye towards cloud implementation ease, scalability, and robustness in a live customer facing production environment. - Provide technical direction and guidance to a small and highly skilled team of junior and senior data scientists embedded in Kanban data squads. These squads deliver products/services in generative AI, data science and data analytics to stakeholders in a large number of business units. Serve as a go-to technical expert in your area of AI expertise. - Work closely with business stakeholders to create impactful and intelligent features/products. Collaborate with other team members including data scientists, data engineers and data strategists. Strategic ownership of all critical end-to-end AI processes. - Administer/maintain performant cloud and on-premises GPU compute resources that train large ML models and provide inference API microservices in production. Requirements / Qualifications - PhD degree related to computer science, machine learning or other AI disciplines is required (consideration will be given to exceptional candidates without advanced degrees). - Demonstrated intellectual firepower as a rapid problem-solver and tech lead. - Advanced programming skills in Python. Strong technical skills in algorithm design/analysis, data structure and SQL. At least intermediate-level mastery of functional/object-oriented software development using modern programming languages such as Scala, TypeScript/JavaScript, Java or C# is a must. - Hands-on proficiency in the use of workflow/map-reduce and stream processing systems such as Spark and Kafka for big-data processing. - 3 or more years of relevant industry experience as a hands-on technical expert in shallow and deep machine learning, with additional specializations in most of the following areas: - Experience in the use of recent proprietary/open-source LLM APIs (such as OpenAI GPT-4, Anthropic Claude 2, Google PaLM 2, or Meta LLaMA 2); software development skills involving multi-agents and prompt engineering using LLM application/data frameworks (such as LlamaIndex and LangChain). - Highly conversant with GPU-accelerated deep learning frameworks (such as PyTorch and TensorFlow). - Demonstrated ability in rapidly adapting, training and deploying state-of-the-art AI models or services in production based on the latest published research papers and open-source code. - Familiarity of Bayesian statistics/inference and Bayesian/causal networks for probabilistic reasoning. - Significant hands-on experience of AWS, Azure, GCP or other public cloud environment. - Excellent mentoring, interpersonal and communication skills for working with both technical staff and non-technical business users. - Experience with Agile/Scrum/Kanban methodologies is a plus. Preferred / Nice to have - Experience with Agile/Scrum/Kanban methodologies is a plus. Selection process / Benefits (if stated) - Not stated ---