About the Institute of Foundation Models (IFM)
The Institute of Foundation Models is a dedicated research lab for building, understanding, deploying, and risk-managing large-scale AI systems. We drive innovation in foundation models and their operationalization, empowering research, education, and industry adoption through scalable infrastructure and real-world applications.
The Role
We are seeking a Community Development Manager to expand the reach and real-world adoption of our foundation models (language, vision, multimodal, and world models) beyond the university environment.
This role bridges the gap between research innovation and practical use, ensuring our models are accessible, well-documented, and actively adopted by external developers, partners, and organizations. The ideal candidate combines technical comfort with strong communication and community-building skills to:
● promote the use of IFM technology,
● foster a vibrant developer and user ecosystem, and
● support adoption strategies.
Key Responsibilities
- Community Development & Engagement
- Build and nurture a developer and user community around IFM's models, APIs, and tools.
- Plan and run workshops, hackathons, webinars, and training sessions to showcase model capabilities and encourage experimentation and adoption.
- Develop partnerships with industry, government, and academic collaborators to promote technology transfer and open innovation around IFM models.
- Represent IFM at external events, conferences, and meetups, championing its models, tools, and initiatives.
- Define and track key community metrics (e.g., active developers, event participation, usage coming from community channels) to understand impact and refine activities.
- Technology Adoption & Support
- Work closely with the Product, Research, and Engineering teams to understand model capabilities, deployment options, and priority use cases.
- Translate complex research outputs into practical applications, example integrations, documentation, and user guides.
- Provide technical onboarding and ongoing support to external developers and partners integrating IFM models and APIs.
- Gather structured feedback from users and partners, and channel it into product and research roadmaps (e.g., feature requests, pain points, documentation gaps).
- Coordinate with DevOps and MLOps teams to ensure external users have reliable access to IFM models (APIs, SDKs, sandbox environments) and know how to use them.
- Content & Knowledge Sharing
- Develop and maintain public-facing resources such as documentation, tutorials, FAQs, example repos, and quick-start guides.
- Create and support content such as blog posts, talks, short videos, and demo showcases that explain “what this model can do” and “how to use it” for different audiences.
- Support the creation of case studies and success stories that highlight impactful applications built on IFM models.
- Contribute to communication materials for product updates, new releases, and adoption milestones, in coordination with Product and Communications teams.
Qualifications & Experience
- Essential
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field.
- 3–6 years of experience in developer relations, technical community building, technology adoption, or adjacent roles (e.g., product, solutions, startup founder/operator with strong external-facing responsibilities).
- Comfortable writing small scripts and demo applications in Python or JavaScript to call APIs, build simple prototypes, and help developers integrate IFM models into their own applications.
- Familiarity with how modern ML models are used in practice (e.g., calling hosted models via APIs, using SDKs, or working with ecosystems such as Hugging Face).
- Experience working with GitHub or similar platforms (issues, pull requests, basic branching) and contributing to documentation and example repositories.
- Strong written and verbal communication skills, with the ability to translate complex technical concepts into clear, accessible language for both technical and non-technical audiences.
- Demonstrated ability to plan, execute, and iterate on community or developer-facing programs (events, workshops, hackathons, pilots) in a fast-moving environment.
- Proven stakeholder management skills, working across multiple internal teams (research, product, engineering, communications) and external partners
- Preferred
- Experience working with common ML frameworks (e.g., PyTorch, TensorFlow, JAX) or model deployment tools (e.g., Docker, Kubernetes, major cloud platforms).
- Prior experience with foundation models (LLMs, multimodal models, or world models) and familiarity with AI/ML research environments.
- Background in AI/ML, computer science, or a related technical field (formal degree or equivalent practical experience).
- Experience in an academic, research lab, or “frontier-tech” environment where research-to-product translation is part of the work.
