Staff Researcher, Machine Learning

Responsibilities:
•Define, lead and collaborate in machine learning research projects, exploring and advancing AI/ML/SL/RL fundamental algorithms and systems for applications across a variety of domains of interest (e.g., chip design, neural architectures, multi-modal learning, computer vision, device design and many engineering scientific applications).
•Support new technology and research initiatives and implement leading-edge proofs of concept following best practices and with an objective to publish research results and to produce potentially high-value patents.
•Develop research lines through in-depth knowledge of trending applications cutting-edge systems and technical advances such as LLMs (e.g., GTP, DeepSeek).
•Keep pace with advances in a broad manner (e.g., Large Foundation Models, AI for Science, RL for DSE and Inverse Design, Computer Vision, etc.), while focusing more deeply in one to three lines of research – all using, primarily, open-source technologies.
•Be a “T”: i.e., with broad knowledge and interest in a large variety of research domains while increasing depth in particular domains in multi-year projects. 
•Collaborate with in-house and academic researchers focused on applications of reinforcement learning and other machine learning technologies in various fields, including computing, micro-architecture, chip, device and materials design.
•Collaborate with management and communicate complex ideas in various internal and external forums. Test ideas and share results effectively, both orally and in writing.
•Lead and contribute to papers and patents as primarily research deliverables.
•Lead more junior researchers including interns, staff and research contractors.

Qualifications:
•PhD in any of the following or related fields: Electrical Engineering, Computer Science, Physics, Operations Research or Mathematics with a strong background in Statistics.
•Solid publication record in two or more top venues in machine and statistical learning. 
•Advanced understanding of technical troubleshooting approaches, tools and techniques, and the ability to anticipate, recognize, and resolve technical problems arising in research involving open-source technologies in collaboration with teams composed of various levels.
•Solid background in research tools, software and system engineering and good understanding of tools of trade and implementation of machine learning systems.
•Deep knowledge of machine learning, statistical learning and reinforcement learning.
•Strong sense of “product” (research) ownership and business impact.
•Eagerness to learn new ideas, technical advances and research tools.
•Excellent oral and written communication skills.

This full-time position base salary range is $146,000 ~ $234,000, depending on job-related skills, years of relevant experience, educational backgrounds, qualifications, and other job-related factors. The range displayed is for position based in San Jose, California. Additional details (bonus, benefits, relocation, etc.) of the compensation package will be provided to candidates during the interview process.