Freeform is looking to solve the problem of scaling the first production-scale, high-quality, and fully-automated metal 3D printing factory architecture using advanced machine learning techniques and data science infrastructure.
Requirements
- Proficient with Python, C/C++ or similar object oriented language
- Proficient in advanced pattern recognition, predictive modeling and deep learning techniques
- Experience with machine learning or data science as it relates to physics or the physical world
- Proficient in data mining and statistical analysis
- Experience with both supervised and unsupervised learning techniques
- Experience with image processing
- Proficient with NoSQL databases, such as MongoDB or Cassandra
Responsibilities
- Design and develop data models used for model predictive control in an advanced production-scale metal 3D printing system
- Integrate data models and physics-based models into a unified simulation framework
- Develop a deep learning framework for modeling the complex physics associated with laser melting printing technology
- Develop unsupervised learning algorithms to correlate data with printed part quality
- Develop methods to correlate process data with geometric features
- Work closely with simulations engineers to create data models to be used to predict the thermo-mechanical response of printed parts
- Develop learning modules for machine health monitoring
Other
- Bachelor's degree in computer science, applied mathematics, machine learning, data science, or similar technical discipline
- 5+ years of experience in advanced machine learning
- Excellent verbal and written communication skills
- Creative thinker able to apply first-principles reasoning to solve complex problems
- Ability to work in a collaborative environment
