Conduct original and cutting-edge research in efficient generative AI: LLMs and multi-modal foundation models, reasoning with LLMs, reinforcement learning, RAG, Agentic AI and others. Provide technical leadership in research and applied projects and guide research directions to best support company objectives. Mentor AI Residents, junior researchers and engineers, fostering collaboration, growth and excellence in a dynamic R&D environment. Lead efforts in transitioning research into production-ready solutions, enabling real-world applications and commercial impact. Publish in top-tier conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ACL, EMNLP, etc). Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. MSc or PhD in Computer Science, Electrical Engineering, or a closely related field. Proven research excellence demonstrated by publications in top-tier AI/ML conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ACL, EMNLP, etc.). Deep expertise in generative AI, large language models (LLMs), multi-modal language-vision models, LLM reasoning, and diffusion models. Familiar with model optimization techniques such as quantization and distillation. Hands-on experience with model development pipelines, including training, fine-tuning, evaluation, and optimization.
