DE&A - AIML - Data Science - Conventional AI - Search

Job description

- Strong foundation in mathematics: linear algebra, probability, stochastics, optimization theory - Expertise in mathematical programming, algorithm design, and optimization techniques - Skilled in formulating complex problems and designing scalable algorithms (e.g. linear/non-linear programming, convex optimization, combinatorial algorithms, etc.) and experience improving algorithms for efficiency and scalability - Deep knowledge of machine learning, deep learning, and statistical modeling - Strong in Graph Theory or Knowledge Graph related architecture and database (e.g. Neo4j, cuGraph) - Hands-on experience with neural networks, transformers, diffusion models, or generative modeling - Familiarity with NLP, computer vision, or domain-specific AI applications - Proficient in model evaluation, validation, and performance metrics - Experience with AI/ML frameworks and libraries (e.g. TensorFlow, PyTorch) - Familiarity with software development practices (version control, testing, GPU accelerated computing) - Strong analytical thinking and problem-solving skills - Ability to derive insights and prove algorithmic effectiveness through rigorous logic and math - Demonstrated creativity in tackling open-ended research and real-world AI challenges - Clear communicator, able to translate complex ideas for technical and non-technical audiences - Effective collaborator in cross-functional teams with researchers, engineers, and business partners - Skilled in writing technical documentation, reports, and academic publications is a plus - Passion for AI advancement and continuous learning - Active interest in emerging AI research, with contributions to publications, open-source projects or conference preferred