Crisalix is the world's leading technology company in 3D imaging and aesthetic simulation. With a global presence across five continents, it empowers some of the world’s most recognized plastic surgeons and clinics to enhance patient trust, visualize treatment outcomes, and deliver exceptional results.
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About The Role
We are looking for a Computer Vision Engineer with a solid background in deep learning and 3D data processing to join our team. You will work on developing and deploying models that understand and reconstruct the visual world, contributing to production‑grade pipelines that take multi‑view 2D images and produce high‑quality 3D reconstructions—from statistical shape models to implicit neural representations and texture synthesis—at the intersection of classical 3D geometry and modern neural approaches.
Responsibilities
Research, prototype, and integrate new deep learning algorithms from recent literature (NeurIPS, CVPR, ICCV, ECCV) to improve 3D reconstruction quality.
Develop and maintain deep learning components for multi‑view reconstruction, landmark detection, segmentation, inpainting, and view‑consistent shape fitting.
Implement and tune custom training pipelines and loss functions, and evaluate their impact on mesh and texture quality.
Design and run quantitative evaluation experiments using metrics such as reprojection error, surface‑to‑surface distance, and perceptual quality scores.
Export and deploy trained models for inference (TorchScript/JIT, Triton Inference Server, etc.).
Required Skills
2–3 years of hands‑on experience in computer vision and deep learning research or applied engineering.
Solid understanding of camera models, projective geometry, and multi‑view geometry (epipolar geometry, camera calibration, reprojection).
Experience training and debugging neural networks end‑to‑end, including custom loss functions, learning rate scheduling, and training stability.
Comfortable with reading and implementing methods from academic papers.
Strong Python skills;
proficiency with PyTorch (primary) and/or TensorFlow.
Comfortable working in a research codebase with complex multi‑stage pipelines.
Fluent or proficient in English (Spanish is a plus).
Preferred (Optional) Skills
Experience with 3D vision techniques (e.G., NeRFs, differentiable rendering, SLAM).
Understanding of implicit surface representations: SDFs, occupancy networks, NeRF/neural radiance fields.
Familiarity with classical 3D fitting approaches: statistical shape models (PCA‑based), ICP, mesh deformation.
Knowledge of differentiable rendering concepts: ray marching, sphere tracing, volume rendering.
Familiarity with libraries such as Open3D, PyTorch3D, or OpenCV.
Experience with experiment tracking tools (MLflow, W&B;) and reproducible training pipelines.
Experience deploying models to production environments, using Docker for reproducibility and scalability.
Understanding of GPU optimization and performance tuning.
Background in geometry, linear algebra, or graphics.
Benefits & Work‑Life Balance
We offer a competitive salary and benefits package, structured onboarding, mentoring, performance reviews, and training plans to help you advance your career. Work‑life balance is supported through a versátil hybrid model: 2–3 days per week in our Barcelona office and remote work for the remaining days.
Equal Opportunity Statement
Crisalix is committed to equality of opportunity for all staff. xhfqzwm Applications from all suitably qualified individuals are encouraged, regardless of age, disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion or belief, and marriage and civil partnerships.
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