Manager of AI Modeling & Inference

Description

Stanford Libraries is seeking a full-time Manager of AI Modeling & Inference to join Research Data Services. The Libraries values are rooted in a commitment of mutual respect, the idea that every member of the staff has something to contribute, and that learning is constant.  We seek a team member who is ready to share their skills and perspectives.

About the Position:

Stanford University Libraries’ Research Data Services is seeking an experienced, technically-adept, forward-thinking library professional to both lead and directly contribute programming effort to our new AI Modeling & Inference group. This role manages two Digital Scholarship Research Developers, leading a group with significant accomplishments in digital humanities projects.  We are looking for an individual who can both design and implement research software, as well as manage a team of experienced colleagues.

Vision

We seek a professional who can foresee the impact of AI on academic research practices — and develop software and services to maximize the positivity of these effects. At the same time, this role must remain clear-eyed about limitations and problems of AI, and offer responsible guidance to colleagues and patrons alike. Balancing these two perspectives will be key to the leadership role we expect the Manager to play.

Mission

Digital research methods rooted in artificial intelligence have increasing visibility across academic disciplines.  While large language models have captured the popular imagination, a host of architectures, techniques and approaches are now available to researchers, spanning from text to audio to image. As a core unit supporting research practice on campus, Research Data Services is building on its experience in domains such as pose detection, text analysis, and handwriting recognition with an aim of extending services in new directions across all disciplines.  The Manager position will play a key role in gathering input, architecting, and implementing these new service offerings.

Collaboration

This role is a member of the management team in Research Data Services, a patron-facing group at Stanford University Libraries supporting geospatial research data, research data curation, data infrastructure, and academic data support.  Due to the relevance of modeling & inference across many domains, we expect this position to play a crucial role in articulating AI research methods across other parts of RDS.  Examples of this might include text recognition on historic maps, vector-space models for reconciling text in a curation context, or re-training Large Language Models on specific historic or literary corpora. 

Beyond Research Data Services, this Manager role is also responsible for ensuring close collaboration on AI projects with other units inside Stanford University Libraries, including those responsible for collections, subject expertise, rare books, digital library systems, and technical services.

 Core Duties:

●     Monitor technology trends and evaluate emerging technologies to recommend for adoption and implementation.

●     Manage the development and rollout of Stanford University Libraries AI services and software for researchers.

●     Propose, conceptualize, design, implement, and develop solutions for difficult and complex research software applications     independently.

●     Propose, conceptualize, design, implement, and develop solutions for difficult and complex applications independently.

●     Oversee testing, debugging, change control, and documentation for major research software applications.

●     Supervise professional staff, as necessary, working on all phases of research software application development projects.

●     Engage in long-term strategic planning.

●     Define complex application development administration and programming standards.

●     Oversee the support, maintenance, operation, and upgrades of applications.

●     Troubleshoot and resolve complex technical problems.

●     Review the physical design of existing systems for optimizing performance.

●     Lead projects, as necessary, for special systems and application development in areas of complex problems.

●     Work with other technical professionals to develop standards and implement best practices.

MINIMUM REQUIREMENTS

 Education and Experience:

●     Bachelor's degree and eight years of relevant experience, or a combination of education and relevant experience.

Minimum Knowledge, Skills and Abilities:

• Ability to quickly learn and adapt to new technologies and programming tools.
• Demonstrated experience in designing, developing, testing, and deploying applications.
• Strong understanding of data design, architecture, relational databases, and data modeling.
• Thorough understanding of all aspects of software development life cycle and quality control practices.
• Ability to define and solve logical problems for highly technical applications.
• Strong communication skills with both technical and non-technical clients.
• Demonstrated experience leading activities on structured team development projects.
• Ability to select, adapt, and effectively use a variety of programming methods.
• Ability to recognize and recommend needed changes in user and/or operations procedures

Other Relevant Knowledge, Skills, and Abilities May Include:

●     Experience with programming and scripting languages such as Python and Javascript. 

●     Experience with AI & ML software libraries, platforms and environments, including PyTorch, Tensorflow, and CUDA. 

●     Familiarity with common digital cultural heritage platforms and APIs, including IIIF (International Image Interoperability Framework)

●     Knowledge of common neural network architectures and approaches, including Transformers-based approaches in textual, visual, and multi-modal contexts.

.The expected pay range for this position is $137,000.00 to $180,000.00 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location, and external market pay for comparable jobs.