Junior Deep Learning Engineer

We are looking for a junior engineer to join the Deep Learning team. You will work across the full model development lifecycle: from generating datasets and training models from scratch, to experimenting with new algorithms and deploying them into production. This is a role where you will grow into an engineer who can bridge research and engineering: from reading a research paper to shipping it to production. Our ideal candidate would have

Quantitative degree: Computer Science, Engineering, Telecos, Data Science, Mathematics, Physics or a related field that involves strong numerical and analytical foundations.

• Deep learning fundamentals: Solid understanding of how models are trained: loss functions, optimization, backpropagation, overfitting, regularization, etc.

• Python and PyTorch: Proficient in Python and hands-on experience training models in PyTorch or another major deep learning framework.

• Practical engineering skills: Comfortable with Git, GitHub (pull requests, code reviews), command line, and the general software development workflow. Should be able to pick up an open-source repo, set it up, and get it running.

• Research literacy: Ability and willingness to read, understand, and implement ideas from academic papers, journals. We also value very positively:

Nice to Have

• Experience with computer vision (image classification, segmentation, landmark estimation, etc.).

• Experience with 3D reconstruction. Parametric models (SMPL), neural fields (NeRF, gaussian splats).

• Experience with generative models (training, fine-tuning, inference). Diffusion, GANs, VAEs, etc.

• Exposure to ML infrastructure and deployment (MLOps, model serving, containerization, CI/CD for ML).

We are a multinational engineering organization focused on people and our product. At Crisalix we work hard, and we have a beautiful project ahead of us to make our company an excellent place to work.