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Postes : Big Data
Research Scientist Intern - Post-Training (Distillation)
Jasper
France
Hybride
EUR 60 000 - 80 000
Plein temps
Il y a 25 jours

Résumé du poste

A leading AI marketing platform is seeking a Research Scientist Intern to develop state-of-the-art open-source text-to-image models. Candidates must be enrolled in a Ph.D. or M.Sc. program and have strong coding skills in Python. This hybrid role is based in Paris and offers competitive compensation along with the chance to work in a vibrant startup environment.

Prestations

Flexible hybrid work environment
Competitive compensation package

Qualifications

  • Experience with sampling techniques for diffusion models.
  • Interest in open-source initiatives with a track record in deep learning.
  • Available for a 6-month internship.

Responsabilités

  • Design and implement methods to improve the sampling speed of diffusion models.
  • Participate in the fine-tuning of large-scale text-to-image models.
  • Document research findings and prepare technical reports.

Connaissances

Experience with distillation techniques for diffusion models
Strong coding abilities in Python
Familiarity with deep learning frameworks (PyTorch, TensorFlow, JAX)
Critical thinking and problem-solving skills
Teamwork skills

Formation

Currently enrolled in a Ph.D. or M.Sc. program in Machine Learning, applied mathematics, or computer science
Description du poste
Location

France

Employment Type

Full time

Location Type

Hybrid

Department

Engineering

Jasper is the leading AI marketing platform, enabling the world's most innovative companies to reimagine their end-to-end marketing workflows and drive higher ROI through increased brand consistency, efficiency, and personalization at scale.

Jasper has been recognized as "one of the Top 15 Most Innovative AI Companies of 2024" by Fast Company and is trusted by nearly 20% of the Fortune 500 – including Prudential, Ulta Beauty, and Wayfair. Founded in 2021, Jasper is a remote‑first organization with team members across the US, France, and Australia.

About The Role

Jasper Research is seeking a highly motivated intern to advance the frontiers of open source image‑generation and image‑editing applications. In this role, you will be instrumental in developing new state‑of‑the‑art open‑source text‑to‑image and image editing models while collaborating closely with our talented team of researchers and engineers. The internship duration is 6 months.

We have historically relied on third‑party existing open‑source image foundational models for its core applications (replace‑background, image uncropping, image relighting …), mastering model fine‑tuning methods. One of the team’s current core projects consists now of building our own open‑weights foundational text‑to‑image model from scratch.

This role is open to candidates located in Paris. It will be a hybrid setup, which requires you to come into the office when necessary.

What you will do at Jasper

As a Research Scientist Intern, you will work closely with our research team to design and implement new methods to improve the sampling speed of diffusion models, such as, amongst others, re-flow, shortcut models or adversarial diffusion distillation. This role offers a unique opportunity to contribute to the development of a foundational open‑source model, addressing challenges in scalability, fidelity, and generalization. You will engage in both theoretical and applied research, collaborating with experts in machine learning, computer vision, and natural language processing. The main goals of this internship are:

  1. Research & Development: Conduct literature reviews, propose and implement innovative methods to accelerate the sampling from diffusion models in the context of text‑to‑image and image editing.

  2. Model Training & Evaluation: Participate in the fine‑tuning stages of the training of large‑scale text‑to‑image models, conduct rigorous ablations, design evaluation metrics, and analyze model performance.

  3. Documentation & Communication: Document research findings, prepare technical reports, and participate in the external communication of the results.

  4. Open Source & Community: Contribute to an ambitious open‑source project, publish research findings, and engage with the broader AI community.

What you will bring to Jasper
  • Currently enrolled in a Ph.D. or M.Sc program in Machine Learning, applied mathematics or computer science (Ph.D, preferred).

  • Experience with distillation and/or improved sampling techniques for diffusion models

  • A genuine interest in the field and a strong motivation to contribute to open‑source initiatives, with a potentially proven track record through personal projects or previous experience in deep learning, especially generative models (e.g., diffusion models, GANs, VAEs, transformers).

  • Strong coding abilities in Python and deep learning frameworks (PyTorch, TensorFlow, JAX).

  • The ideal candidate will possess a strong critical thinking and problem‑solving mindset, coupled with excellent teamwork skills.

  • Being available for period of 6 months.

Nice to have

  • Strong programming Python skills, including software engineering best practices to produce high‑quality code.

  • Experience with distributed training and large‑scale systems on GPU clusters

  • Experience with large‑scale data processing

  • Contributions to open‑source projects.

  • Proven track record of achieving significant results as demonstrated by first‑authored publications in major conferences and journals such as CVPR, ECCV, ICCV, ICLR, NeurIPS

Benefits & Perks
  • Flexible, hybrid work environment. Our office is based at Station F in Paris, the vibrant hub of the French startup ecosystem. Our efficient and lean team at Station F thrives on innovation and collaboration.

  • Competitive compensation package

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* Le salaire de référence se base sur les salaires cibles des leaders du marché dans leurs secteurs correspondants. Il vise à servir de guide pour aider les membres Premium à évaluer les postes vacants et contribuer aux négociations salariales. Le salaire de référence n’est pas fourni directement par l’entreprise et peut pourrait être beaucoup plus élevé ou plus bas.

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