Senior Machine Learning Engineer
Confirmed live in the last 24 hours
Freeform

11-50 employees

Autonomous metal 3D printing with software-defined factories
Company Overview
Freeform offers a unique work environment that is at the forefront of metal 3D printing, utilizing autonomous factories powered by advanced sensing, real-time controls, and data-driven learning to deliver high-quality parts swiftly and cost-effectively. Their competitive edge lies in making large-scale 3D printing accessible to various industries, which positions them as an industry leader. The company culture is centered around a shared mission to radically alter manufacturing processes, providing employees with the opportunity to contribute to this transformative change.
Industrial & Manufacturing
Data & Analytics
Hardware

Company Stage

Seed

Total Funding

$48.7M

Founded

2019

Headquarters

, California

Growth & Insights
Headcount

6 month growth

9%

1 year growth

45%

2 year growth

118%
Locations
Los Angeles, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Data Science
Data Structures & Algorithms
CategoriesNew
AI & Machine Learning
Applied Machine Learning
Deep Learning
Requirements
  • Bachelor's degree in computer science, applied mathematics, machine learning, data science, or similar technical discipline
  • 5+ years of experience in advanced machine learning
  • 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
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
  • Work with software engineers to deploy data science algorithms in production software
  • Guide software engineers to develop the big data infrastructure required to collect and process large amounts of production printing data
  • Develop data models used for the end-to-end automation of an advanced metal 3D printing platform