Geometric Machine Learning Engineer (2022 Graduates)
Why Link3D?
Link3D is the leading industrial 3D printing enterprise SaaS startup helping businesses digitally transform manufacturing strategies to support their supply chains. Some of the challenges Fortune 500, Tiered Contract Manufacturers and Service Bureaus face to ensure industrialization of 3D printing reside in the industry’s ability to achieve production repeatability and supply chain optimization at scale.
By joining Link3D, you will have an opportunity to make an impact across the Aerospace, Automotive, Medical, Industrial and Consumer Product sectors as they adopt enterprise workflow, MES and QMS software to achieve Industry 4.0.
Job Description
As a Geometric Machine Learning Engineer, you will leverage your skills in Deep Learning, Data Engineering, and Computer Vision to create solutions that will improve the end to end additive manufacturing workflow for our industrial 3D Printing customers. This position will work with the R&D team to develop cutting edge machine learning models to solve novel problems in the additive manufacturing space. Responsibilities will include researching and implementing state of the art Deep Learning architectures, constructing machine learning pipelines, and working with real world datasets for regression, classification, and anomaly detection applications.
Skills and Qualifications
Required:
- Experience working with a least one of the following 3D Data formats: CAD, STL, mesh, voxel, or point clouds
- Proficiency building machine learning models for applications including but not limited to detection, segmentation, regression, and spatio-temporal analysis
- Proficiency with at least one of the following: Python, Java, C/C++
- Proficiency with PyTorch, Tensorflow, or other Deep Learning framework
- Project experience implementing a high performance neural network in a NLP, image, or geometry based application
- Mathematical aptitude and strong problem-solving skills
- Demonstrated ability to deconstruct and solve complex problems
Good to have:
- M.S. or Ph.D in CS, CE, or related field with an AI or computer vision concentration
- Knowledge of discrete geometry and shape analysis
- Experience with Deep Learning on 3D or geometric data
- Project experience using machine learning for regression tasks
- Experience building Deep Learning pipelines
- Experience working with CT data
- C/C++ algorithm development experience
- Additive manufacturing experience
- Proficiency with fundamental computer vision algorithms
- Experience working with AWS, Azure, or other cloud system
About Link3D
Enabling Industry 4.0 digital manufacturing strategies at scale is the core of Link3D’s innovative technology platform. By leveraging partnerships with leading machine manufacturers and software vendors, Link3D continues to be a proven leader in advancing additive manufacturing by positioning itself as the operating systems for smart manufacturing.
Founded in 2016, Link3D is headquartered in Colorado, with its software development team in New Jersey. Link3D has enabled enterprises including GE, EOS, 3D Systems, PostNord, Fraunhofer and other major additive manufacturing institutions to scale their additive manufacturing floor with AM workflow software, MES and QMS systems.
Why join our team?
At Link3D, we all contribute to a respectful work environment where we share ideas and encourage each other to think creatively. We are a collaborative, diverse and dynamic group of individuals ready to embark on our next chapter of growth.
Do you want to be part of a culture that is inclusive, inspiring, and allows you the autonomy to be creative in your work? If so, we invite you to join us on our adventure!
Benefits And Perks Include
- Healthcare that fits your needs – We offer medical and dental plan options that provide coverage to employees and dependents.
- 401(k) – Join the team and we will immediately invest in your future.
- Flexible vacation plan
- Potential for company equity and performance-based bonuses
- Location preference: New Jersey, Princeton
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