Lumafield was founded in 2019 to upgrade manufacturing.
We are engineers with deep experience across the product development cycle, from initial ideas to shipping hardware, across industries and specializations, who became frustrated by the cost and complexity of modern manufacturing. So we decided to upgrade it.
Engineers make million-dollar decisions every day, and they need tools that give them the greatest possible insight into their products. By offering unprecedented visibility into products, as well as AI-driven tools that highlight problems and generate quantitative data, Lumafield promises to revolutionize the way complex products are created, manufactured, and used across industries. We started with industrial CT scanning, which for us was the most valuable but underutilized tool in the manufacturing toolbox, enabling us to rapidly inspect essential components non-destructively.
We rebuilt the whole system, from X-ray capture, to computer vision analysis, to web-based collaboration, to the entire business model, making the most advanced manufacturing tech more accessible to every industry. Our company, like our platform, is designed for upgrades. We’re building for greater intelligence, autonomy, and speed. For deeper vision, operational excellence, and powerful insights. And then we'll upgrade it all again.
Lumafield is headquartered in San Francisco, CA. and has an office in Cambridge, MA.
About the role:
Lumafield has the world’s largest dataset of real manufactured products. Encoded into this dataset are deep representations of design and manufacturing rules. Automating manufacturing is a key pillar in Lumafield’s ultimate vision to transform all of design and manufacturing.
As an Applied Research Scientist, Manufacturing, you will lead technical development of our manufacturing automation capabilities. This is a uniquely applied role: you will wear steel toed boots while writing code in manufacturing facilities.
What you'll do:
Lead technical development of methods to automate manufacturing processes like die casting, injection molding, CNC machining, and more.
Design experiments, implement them, and iterate until you have a manufacturing process autonomous.
Integrate robots, manufacturing equipment, and CT scanners in our SF manufacturing lab
Interface with customers to define pilot programs.
Travel to customer manufacturing sites all around the world.
About you:
Are excellent at prototyping and 0-1 problems.
Have applied machine learning and optimization experience.
Have strong instincts for experiment design and are deeply empirical.
Are AI native and can apply the tools with high leverage.
Are well-versed in scientific computing and simulation packages.
Are extremely independent and can give unstructured problems structure and direction.
5-10 years of experience in a relevant technical field.
Bonus:
Advanced degree in machine learning, optimization, or a relevant discipline.
Background or experience in design, manufacturing, or physical hardware.
Familiarity with BREP/analytical geometry or CAD kernels.
PLC programming experience.
A portfolio of work that you can share that is relevant to this role.
Additional Information
Lumafield offers both competitive cash and equity compensation, as well as a health & wellness stipend, 401k, parental leave, flexible PTO, commuter benefits, company wide events and more!
Lumafield is committed to building a team that represents a variety of backgrounds, perspectives, and skills, because the more inclusive we are, the better our work will be. Do you feel like your skills don’t meet every single requirement listed? We encourage you to apply anyway – If you’re excited about our technology, the opportunity, and are eager to learn more we’d love to hear from you!
In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital domestic partner status, sexual orientation, gender identity, disability, genetic information or veteran status.
Reach out if you want to be a part of what we are building.
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