Machine Learning Engineer
Emphasis: Statistical models for estimation, modelling, and simulating human body shape & pose
Meshcapade is a startup creating realistic human avatars for use in research, apparel, biomechanics, virtual reality and film. Using machine learning and computer vision, we model the nuances of human shape and movement. We build automation from 3D & 4D scans, RGB-D sequences, Mocap, IMU and image data. Our methods derive from SOTA research and we bring realistic human models to life in everyday environments. Our core product, digidoppel, is a consumer-facing platform for the creation, modification, and delivery of our models and related assets.
What we offer
You will work closely with the founders to help build the core products of a tech startup, with the opportunity to drive design from the ground up. We are a team of passionate creators from a variety of backgrounds, seeking to change how people generate, think about, and make use of digital avatars. Salary will be commensurate with experience. Our offices are based in Tübingen, Germany and we offer relocation support. Remote working options are also available.
You will help define the technical direction on improving our internal software and methods using the SMPL Model and related technologies for human body shape & pose estimation. You will research, develop and test improvements for our existing research-based code base as well as develop new methods for non-rigid shape analysis and statistical modelling of body shapes, as well as recognition, capture and analysis of motion of humans (and eventually animals too!).
Solid understanding of statistical human body models like SMPL
Experience developing optimization techniques for fitting SMPL or similar models to sensor-based data (RGB-D, images, mocap or 3D scans) or training new machine learning models for pose & shape estimation
5+ years experience developing in Python and/or C++
Master's or PhD degree in computer science or another related field
Proven track record of publications on topics related to statistical body modelling, estimation or motion tracking methods
Strong understanding of computer vision and machine learning techniques
Excellent written and oral communication skills
Experience in related topics such as 3D meshes, point-cloud processing, neural networks, classical optimization, etc.