AI Research Scientist

About Us: webAI is pioneering the future of artificial intelligence by establishing the first distributed AI infrastructure dedicated to personalized AI. We recognize the evolving demands of a data-driven society for scalability and flexibility, and we firmly believe that the future of AI lies in distributed processing at the edge, bringing computation closer to the source of data generation. Our mission is to build a future where a company's valuable data and intellectual property remain entirely private, enabling the deployment of large-scale AI models directly on standard consumer hardware without compromising the information embedded within those models. We are developing an end-to-end platform that is secure, scalable, and fully under the control of our users, empowering enterprises with AI that understands their unique business. We are a team driven by truth, ownership, tenacity, and humility, and we seek individuals who resonate with these core values and are passionate about shaping the next generation of AI. About the Role: The AI Research Scientist will contribute to webAI’s development of next-generation AI models and systems. In this role, you will design, train, evaluate, and optimize cutting-edge machine learning models including large language models, multimodal architectures, and on-device inference systems. You will work closely with research leadership, applied AI teams, and platform engineering to advance scientific discovery while ensuring that innovations translate into real-world impact. This is a hands-on research role for someone who loves experimentation, solving complex problems, and building AI that is powerful, efficient, and privacy-preserving. Responsibilities: - Design, train, and optimize machine learning models including LLMs, multimodal models, transformers, and diffusion architectures - Conduct research on model efficiency, quantization, compression, and on-device deployment - Prototype novel model architectures, training methods, and inference strategies for distributed AI - Develop and evaluate benchmarks, datasets, and experimental frameworks to test model performance - Collaborate with engineering teams to integrate research findings into production systems - Stay current on leading research in deep learning, generative AI, and distributed ML - Analyze experimental results and communicate insights clearly to technical and non-technical stakeholders - Document research findings, contribute to internal papers, and present technical work across the organization - Identify emerging technologies and propose research directions aligned with webAI’s strategic priorities Qualifications: - 4+ years of experience (can be graduate research) in machine learning research, AI model development, or related fields - Strong expertise in deep learning architectures including transformers, CNNs, RNNs, and diffusion models - Hands-on experience training and fine-tuning large-scale models - Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX - Experience building datasets, designing experiments, and validating ML model performance - Deep understanding of optimization techniques including quantization, distillation, pruning, and hardware-aware training - Strong problem-solving skills and ability to work independently on complex research tasks - Effective communication skills for presenting research findings to diverse audiences - Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field Preferred Skills - Master’s or PhD in Machine Learning, Computer Science, AI, or a related field - Experience with distributed training, edge inference, or on-device ML - Research experience in generative AI, reinforcement learning, or multimodal learning - Familiarity with privacy-preserving ML techniques such as federated learning - Experience contributing to academic publications, patents, or open-source ML projects - Comfort operating in a fast-paced, high-growth startup env