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IFM

Community Development Manager

IFM is hiring a Community Development Manager in Abu Dhabi, United Arab Emirates. Level rates it ; you can apply on IFM.

Level's read on this job

  • Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The posting mentions Hugging Face, PyTorch and TensorFlow among its tools and skills.
  • Level classes it as a mid-level role.
  • IFM has 43 other open roles on Level.

AI in this role

Hugging FacePyTorchTensorFlowJAX
ml-ops
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.

How we rate this

Community Development Manager at IFM rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsHugging FacePyTorchTensorFlowJAX

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. Walk me through how you've used Hugging Face in your day-to-day work.
  3. What are the limits of PyTorch that you've run into, and how did you work around them?
  4. What's a project where you used TensorFlow hands-on?
  5. Walk me through how you've used JAX in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: ML Ops, Hugging Face, PyTorch, TensorFlow, and JAX. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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