A strong academic foundation matters to us. We’re looking for candidates with a degree in Computer Science, Electrical Engineering, Mathematics, Physics, or a related technical field. A Master’s or PhD in machine learning or a related area is a strong plus — but not a requirement if you can demonstrate equivalent depth through your work.
More than years of experience, we care about demonstrated ability to build. You should be able to point to models you’ve trained, fine-tuned, or shipped — whether in a professional setting, a research context, or on your own. A strong GitHub and/or Hugging Face profile is a significant advantage.
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Hands-on experience training or fine-tuning deep learning models that are used in production.
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Strong Python skills and experience with ML frameworks (PyTorch or JAX preferred)
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Comfort with the full model development cycle: data pipelines, experiment tracking, evaluation, deployment and scaling.
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Solid understanding of modern model architectures and when to apply them
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Experience with the Hugging Face ecosystem (Transformers, Datasets, Hub) is a strong plus
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Ability to work autonomously, make decisions under uncertainty, and ship without waiting for perfect conditions
You actively use AI tools in your own workflow — not as a novelty, but as a genuine productivity multiplier. You stay current with the state of the art and know how to apply the latest research to real product problems.
You communicate clearly and directly. You can explain technical decisions to non-technical stakeholders, flag blockers early, and collaborate effectively in a small, fast-moving team.