Member of Technical Staff, Research (2026 PhD New Grad) - Seattle

THE ROLE

This role is designed for researchers finishing their PhD who want their work to reach production, not just publication. As a Member of Technical Staff on the Research team, you'll push the boundaries of generative AI, advancing LLMs and multimodal systems through foundational research. Your work will enhance model efficiency, accuracy, and scalability, directly shaping our high-performance AI infrastructure.

You'll be paired with a senior researcher as a mentor and given a real research problem from day one. You'll collaborate with top experts in deep learning, distributed systems, and optimization, and you'll see the models you help create deployed by some of the world's leading companies — often within weeks rather than years.

We welcome candidates who have completed within the last 6 months, or expected completion by December 2026.

KEY RESPONSIBILITIES

• Conduct foundational research to advance the capabilities, efficiency, and reliability of LLMs and multimodal systems

• Design, implement, and evaluate novel model architectures, training methods, and optimization techniques

• Work alongside engineering teams to transition research prototypes into production-grade systems

• Analyze empirical results, identify performance bottlenecks, and iterate quickly to improve model quality

• Bring ideas and emerging directions from your doctoral research into our internal research agenda

MINIMUM QUALIFICATIONS

• PhD completed within the last 6 months, or expected completion by December 2026, in Computer Science, Machine Learning, Computational Physics, Mathematics, Electrical Engineering, or a similar field

• Research background in Artificial Intelligence, Machine Learning, Physics, or a related area, demonstrated through your dissertation, publications, or research projects

• Experience solving analytical problems using analytic and quantitative approaches

• Experience communicating research to audiences with different backgrounds

• Proficiency coding in Python, C/C++, or other similar languages

• Hands-on experience with ML frameworks such as PyTorch, JAX, or TensorFlow

PREFERRED QUALIFICATIONS

• First-authored publications at top-tier peer-reviewed conferences or journals (NeurIPS, ICML, ICLR, MLSys, or similar)

• Industry research internships, or open-source contributions to ML systems, model training, or inference projects

• Research or engineering experience demonstrated via grants, fellowships, patents, or coding competitions

• Experience with large-scale model training, distributed systems, GPU kernel development, or inference optimization

• Experience taking research code beyond the prototype stage