AI Research Scientist

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

Requirements

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

Nice to have

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 environment

Benefits

Competitive salary; Comprehensive health, dental, and vision benefits package; 401(k) match; Equity options; $200/month Health & Wellness stipend; Continuing Education support; $500/year Function Health subscription; Free parking for in-office employees; Flexible Time Off (FTO); Parental leave for eligible employees; Supplemental life insurance