Director, Machine Learning

Summary

Reporting directly to the Executive Director of CCAT, the Director of Machine Learning sets and steers CCAT’s AI and machine learning research agenda. This is a foundational role responsible for building the rigor, culture, and output of CCAT’s ML lab: from research design and model development to the responsible translation of technical work into meaningful creative applications.

CCAT’s institutional thesis holds that artists need direct technical understanding of the technologies shaping culture, not merely proximity to technologists or surface-level tool access. The ML Director gives that thesis its technical spine. Their work defines what is actually possible at CCAT, and ensures that possibility is grounded in methodological integrity, not instrumentalized for output.

This is a senior research leadership role calibrated to attract candidates operating at the principal or staff level in industry ML research, or at the equivalent rank in academic research. The combination of deep technical expertise, institutional fluency, and genuine creative-sector engagement required for this role is exceptionally rare in the current talent market and is reflected accordingly in CCAT’s compensation approach.

This is not a support role. The ML Director is a co-contributor of CCAT’s program, a voice in its curatorial logic, and a role model for the kind of fluency CCAT aspires towards with everyone it engages.

This is a grant-funded position. Continued employment is contingent upon the availability of funding from the CHANEL Culture Fund. There is no guarantee of continued employment beyond the period for which funding has been secured.

Essential Job Functions

• Research Agenda and Lab Direction
  
  

The Director is the primary intellectual and operational steward of CCAT’s ML research function. Responsibilities include:

• Define and evolve CCAT’s ML research agenda in alignment with the Center’s annual priorities and institutional thesis.
• Design and oversee the lab’s experimentation plan: research questions, development pathways, evaluation criteria, and propose publication or dissemination strategies.
• Establish and maintain methodological standards for all ML work conducted under CCAT’s name, including demos, prototypes, and public-facing technical claims.
• Conduct feasibility and risk review for proposed projects and programs where ML is a core medium or technical component.
• Stay current with developments across model training, large language models, neural networks, and computing infrastructure, and bring that knowledge actively into CCAT’s program planning.
• Familiarity with spatial computing, XR technologies, or robotics is a strong asset and will inform CCAT’s expanding technical scope.
• Interdisciplinary Program Collaboration
  
  

CCAT’s program is developed through interdisciplinary co-authorship. The ML Director is a full member of the Program Working Group and contributes technical perspective across all stages of program development.

• Participate in Working Group co-development of program concepts, research thesis, and curatorial framing.
• Surface technical opportunities, constraints, and risks that shape what CCAT can responsibly commit to publicly.
• Partner with the Director of Moving Image, Senior Curator, and Consulting Producer to translate research into public programs, exhibitions, and knowledge-sharing outputs.
• Serve as a required input on all programs where ML is a core medium or where public-facing claims about machine learning are involved.
• Build and sustain relationships with peer research institutions, university ML labs, and external technical communities; support informal peer review of CCAT’s research output and help position the center’s work within the broader field.
  
  

Note on Structure: the Director of Machine Learning serves as a core member of CCAT’s Program Working Group, an explicitly non-hierarchical decision-making body comprising the two Directors, and the Senior Curator. The Working Group co-develops program concepts, research thesis, and curatorial framing, operating under the ED’s mission frame and approval authority. This structure is designed to prevent discipline-first hierarchies and to ensure that CCAT’s public programming reflects its identity as a research and experimentation center.

• Fellows Program Leadership
  
  

The Director selects, mentors, and structures CCAT’s ML faculty fellows and post-graduate fellows, whose applied research work helps realize the lab’s broader agenda.

• Define fellowship parameters: research focus, time commitment, outputs, and integration into CCAT’s program and lab.
• Identify and recommend faculty fellows whose work advances CCAT’s research priorities.
• Mentor fellows as practitioners and emerging researchers, fostering independent inquiry within CCAT’s collaborative model.
• Ensure fellows’ work contributes meaningfully to CCAT’s documentation, publications, and public-facing program outputs.
• Educational Engagement and Institutional Integration
  
  

CCAT is at CalArts, and the ML Director’s role carries a genuine pedagogical dimension. Comfort in a higher education and arts education environments is essential.

• Support the interdisciplinary dimensions of CCAT’s visiting artist program, contributing technical context and perspective to artist engagements.
• Contribute to CCAT’s annual symposium, white paper publications, and other knowledge-sharing outputs as a technical author and co-thinker.
• Represent CCAT’s technical vision to external partners, funders, and field participants with the same fluency applied internally.
• Cultivate external institutional relationships that provide peer-level scholarly and technical feedback on CCAT’s ML research — establishing independent quality benchmarks in the absence of a traditional academic review structure, and strengthening CCAT’s credibility and reach within the research community.
  
  

All other duties as assigned.

Qualifications

DESIRED COMPETENCIES

• Senior-level or principal-level expertise in machine learning research and development, with independent research authorship and a demonstrated ability to set (as well as execute) a technical agenda. Experience at this level in both research and applied industry or academic contexts is strongly preferred.
• Track record of rigorous, original technical work, in academic, industry, or independent research contexts.
• Genuine openness to interdisciplinary inquiry and demonstrated ability to collaborate across technical and non-technical communities.
• Strong communicator capable of translating complex technical concepts for artists, humanists, and non-specialist audiences without condescension or oversimplification.
• Comfort working within a higher education environment, including a willingness to engage with Art students and support emerging researchers.
• Familiarity with spatial computing, XR technologies, or robotics preferred.
• Experience managing researchers or fellows; ability to mentor without micromanaging.
• Commitment to responsible and ethical AI development practices. Fluent in standard open-source frameworks (e.g., PyTorch, TensorFlow).
• Programming fluency in Python, C/C or Rust.
• Adherence to CalArts and CCAT institutional policies on AI use, and active participation in ongoing policy conversations to help maintain and evolve those standards as the field changes.
  
  

ADMINISTRATION

• On-campus presence at CalArts (Valencia, CA) required; specific cadence to be agreed upon with the Executive Director.
• Active participant in the CCAT Program Working Group.