AI Applied Scientist

19 hours ago

bangalore, India G42 Full time

About the Role We’re seeking an inventive AI Applied Scientist to us and drive breakthroughs in agentic AI architecture. You will conduct cutting-edge research, design novel algorithms, and help translate state-of-the-art theory into practical solutions. Your work will shape the future of autonomous agents, creative reasoning, and predictive intelligence. This is a hybrid role between research and applied development—working with the best minds in AI and contributing meaningful innovation with real-world impact. Key Responsibilities •End-to-end ownership of products / features: Experience of delivering product features / products •Manage a small pod for product / feature delivery: Manage a team of 4-6 people to deliver the required features / products •Mentorship: Guide and support AI engineers, elevating team expertise and scientific rigor. •Cross-functional Collaboration: Work with engineers, data teams, and evaluation partners to integrate research outputs into evaluation pipelines and prototypes. •Research & Architect Novel AI Systems: Collaborate with the G42 Technical team to conceive and implement advanced agentic AI architectures. •Algorithm Development: Build new algorithms for reasoning, planning, causal inference, and trend forecasting— anchored in the latest scientific advances. •Innovate and Ideate: Drive ideation and design of new models, expanding the frontier of AI capabilities. •Publish and Present: Contribute high-impact research outcomes to top-tier academic venues and technical outlets. Qualifications •Academic Credentials: Master's or Ph.D. in AI/ML, Computer Science, or a closely related field. •Experience Level: 6 years+ (negotiable if the candidate is good and experience is less than 6 years) of relevant work experience, ideally at the intersection of research and applied AI development. • Technical Expertise: Strong foundation in LLMs and Multimodal models, and techniques such as reasoning, planning, causal inference, forecasting. Proficiency in programming languages and frameworks commonly used in AI research (e.g. Python, PyTorch). Experience in designing and evaluating AI models and algorithms, with a research-driven mindset. Scholarly Output: Record or strong potential for publishing in high-impact conferences or journals. Soft Skills: Excellent problem-solving and critical-thinking abilities. Effective communication skills, capable of both mentoring and translating complex concepts for diverse audiences.

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