Responsibilities

• Conduct cutting-edge research in LLMs, multimodal models, and resource-constrained settings, contributing to the company's overall research agenda.
• Develop and implement novel algorithms, techniques, and models using state-of-the-art approaches such as fine-tuning methods, federated learning, and knowledge distillation.
• Collaborate with the research team, as well as external partners, to enhance our research capabilities and drive innovation.
• Publish research findings in top-tier conferences and journals such as NeurIPS, ICML, and ACL, and present at industry events to showcase our advancements and maintain our position as an industry leader.
• Provide technical guidance and mentorship to junior researchers and engineers, fostering a culture of collaboration and continuous learning.
• Stay up-to-date on industry trends, competitor activities, and emerging technologies to ensure our research remains relevant and cutting-edge.

Required Qualifications

• PhD in Computer Science, Artificial Intelligence, or a related field.
• 4+ years of experience in AI research, with a focus on LLMs and multimodal models.
• Strong track record of published research and conference presentations in relevant fields, particularly at top-tier conferences such as NeurIPS, ICML, and ACL.
• Proficient in Python, TensorFlow, PyTorch, and other relevant AI and machine learning frameworks.
• Experience with advanced techniques in fine-tuning, federated learning, and knowledge distillation for LLMs and multimodal models.
• Strong problem-solving skills and the ability to work in a fast-paced, dynamic environment.
• Excellent communication and collaboration skills, with experience mentoring and guiding junior team members.