Research Engineer

Job Description

This position has been deemed critical by the School of Engineering Dean’s Office and is exempt from the hiring freeze.

For Stanford University employees, please apply through the Opportunity Marketplace within Sequoia.

Note: This is a 3-year fixed term position.

Work Arrangement:

This position is eligible for a hybrid work arrangement with a minimum of 3 days/week working at the Stanford main campus, subject to operational needs.

Budgeted Salary:

The budgeted base salary range for this position is $125,000 to $225,000 per annum.

The School of Engineering

Stanford Engineering has been at the forefront of innovation for over a century, creating pivotal technologies that have transformed the worlds of information technology, communications, health care, energy, business and beyond. Our faculty and students are creative risk-takers who pursue excellence across a breadth of disciplines. Our alumni include some of the world's most successful leaders in technology and business. Our staff are critical to enabling Stanford Engineering to accomplish its mission: seeking solutions to some of the world's most urgent challenges and educating leaders who will make the world a better place through the power of engineering principles, techniques and systems.

Founded in 1965, the Stanford Computer Science (CS) Department continues to lead the world in computer science research and education. Throughout the past five decades, the Stanford CS Department has influenced society at levels that remain without parallel among academic institutions. Its spin-offs are among the most successful corporate ventures in the world, and many of the leaders in academic and corporate research world are graduates of the Stanford CS Department.

Prof. Jure Leskovec is inviting applications for a Research Engineer position in the Stanford Machine Learning group. Our research develops next-generation AI systems for scientific discovery and complex structured data. We build foundation models and AI agents that can learn, reason, and generalize across large-scale relational, multimodal, and multi-scale systems—from databases and knowledge graphs to molecules, cells, patients, and populations. Current research directions include foundation models for biology and the AI virtual cell, autonomous AI scientists and agents, relational and graph foundation models, multimodal and multi-scale learning, and new architectures for reasoning over structured data. A major focus is AI for biomedicine, including understanding biological systems, precision medicine, and accelerating drug discovery.

We are seeking a highly motivated Research Engineer with a strong background in machine learning and computer science to join our group and contribute to ambitious, high-impact research.

CORE DUTIES:

• Play an active role in the execution and coordination of the group’s research activities, helping advance projects from initial ideas through experimentation, publication, and dissemination.

• Responsibilities will include contributing to research and publications as well as preparing grant proposals, progress reports, and final reports.

• You may also help mentor postdoctoral scholars, graduate students, and undergraduate researchers, and contribute to the development and teaching of graduate-level courses in machine learning and related areas.

• The position is intended for someone who can combine strong technical research skills with the ability to help lead and organize a broad academic research program.

Qualifications:

EDUCATION AND EXPERIENCE:

• PhD in Machine Learning or Computer Science or equivalent experience.

KNOWLEDGE, SKILLS AND ABILITIES:

• Excellent problem solving, written and oral communication skills.

• Strong organizational skills.

• Ability to lead and manage projects with a high degree of independence.

Desired Qualifications:

• Familiarity with government funding agencies and academic research funding process.

• Experience with teaching graduate level courses.

• Research experience related to AI & machine learning.

• Prior experience in technical writing.

• Capacity to communicate information in a manner easily understood.