Staff Research Engineer, Generative AI, Cloud AI Research, Co-Scientist

• Own projects end-to-end, from initial scientific research concepts through software design, testing, deployment, and performance analysis.
• Build and deploy agentic AI systems, implementing multi-agent prompting techniques and asynchronous task execution frameworks.
• Drive technical decisions and full-stack software development using Python, C++, and Google's core back-end components.
• Design and establish robust evaluation pipelines, automated test suites, and diagnostic datasets to measure agent performance under extreme scale.
• Collaborate on research with Google DeepMind, Google Research, and university labs to solve complex scientific problems, while mentoring junior engineers and advocating engineering quality.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development, including testing and launching software products.
• 3 years of experience optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 2 years of experience with GenAI techniques (e.g., Large Language Models (LLMs), Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).

Preferred qualifications:

• Master's degree, PhD or Postdoc in Computer Science, Applied Math, Computational Sciences, or a related scientific discipline.
• 3 years of experience with deep learning frameworks (e.g., JAX, TensorFlow, PyTorch) and algorithmic background.
• 1 year of experience in a technical leadership role.
• Experience driving independent, research-adjacent software development and translating academic theories into scalable products.
• Record of technical or scientific contributions to complex, large-scale projects.

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development, including testing and launching software products.
• 3 years of experience optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 2 years of experience with GenAI techniques (e.g., Large Language Models (LLMs), Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).