AI Research Scientist

webAI•Austin, TX

43d

About The Position

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.

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 Haves

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

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