ML Open Source Lead

Ideogram
Onsite

About The Position

The open-source ML leader serves as a bridge between Ideogram’s internal research teams and the broader AI ecosystem. This person will be tasked with turning foundational research into usable, high-quality public tooling, while actively growing and maintaining a healthy developer community.

Requirements

  • Advanced degree or equivalent research experience in Machine Learning or Deep Learning, or a related field
  • Uses personal and professional platforms to amplify open research initiatives and invite collaboration
  • Strong hands-on experience in Python and ML research libraries such as PyTorch, JAX, or TensorFlow
  • Familiarity with LLMs and modern deep learning architectures (e.g., Transformers, diffusion models, reinforcement learning with human feedback)
  • Experience publishing research or working on open-source projects in ML, computer vision, or NLP
  • Excellent communicator who enjoys engaging with the developer and open source community
  • Passion for open source projects and community-driven research/tooling
  • Great communication skills
  • Willing to dive into things quickly, pick up new tools from the open source community, and enjoys exploring new ideas

Responsibilities

  • Define and execute a vision for releasing open model weights, methodologies, and code.
  • Oversee GitHub and Huggingface repositories.
  • Champion open science by building open source demos (e.g. implementing lora fine-tuning for our models), writing technical blogs, answering questions from the community, and presenting at conferences.
  • Partner with model providers, internal engineers, and external contributors to push AI accessibility forward.
  • Convert internal, proprietary implementations into polished open-source code, ensuring quality, reproducibility, and ease of use for the community.

Benefits

  • Competitive compensation and equity
  • 4 weeks of vacation
  • Comprehensive health, vision, and dental coverage
  • RRSP/401(k) with employer match up to 4%
  • Top-of-the-line tools and tech
  • Daily in-office lunches and dinners
  • Autonomy to explore and experiment
  • Access to compute/resources for new ideas, large-scale experiments, or research with a clear business or creative use case
  • Culture of learning and growth
  • Mentorship
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