Research Engineer, Design to Manufacturing

Vizcom•San Francisco, CA

12h•$250,000 - $450,000•Onsite

About The Position

Vizcom is a Series B company that provides a platform for design teams at major companies like Nike, GM, New Balance, and Hasbro, enabling them to sketch, render, color, and export designs. The company focuses on bridging the gap between digital designs and physical products, addressing challenges in areas like solid meshes, editable surfaces, manufacturable geometry, and softgoods production. This role is central to Vizcom's mission of 'make it real,' aiming to create files that factories can accept, moving beyond just creating visually appealing renders.

Requirements

Deep expertise in at least one link of the chain (geometry processing, appearance and material modeling, cloth or textile simulation, computational fabrication).
Working fluency across other links of the chain.
Hands-on experience with modern generative or reconstruction methods.
Engineering skill to turn research papers into functional pipelines.
Comfort being a pioneer; starting a new research log and direction.
Judgment that prioritizes whether a generated model could physically exist over its visual appearance.

Nice To Haves

Exposure to CAD kernels, B-rep, solid modeling, or Class-A surfacing.
Experience with color science, appearance capture, or knit and textile engineering.
Experience with physical simulation that runs at product speed, such as cloth, FEA, or structural sanity checks.
Experience shipping a physical product or witnessing a product fail during the handoff process.

Responsibilities

Own the visualization-to-actualization chain as an open research direction with a product attached.
Determine which links in the chain to attack first, which representations to bet on, and define what factory-acceptable means, written down and measured.
Focus on geometry processing, potentially starting with generated 3D to editable, manufacturable geometry, including parametric surfaces, curve extraction, and CAD handoff.
Address material and color specifications, moving from rendered appearance to real-world standards.
Tackle softgoods challenges such as pattern flattening, seam logic, and knit processes.
Integrate manufacturability into the loop, considering properties like manifoldness, tolerances, and wall thickness as part of the generation process, not just a repair pass.
Develop the output layer, creating artifacts like CAD files, pattern pieces, and tech packs that downstream teams consume.
Define the evaluation criteria for factory-acceptability, specific to different industry verticals.
Manage customer pilots and contribute to the flywheel bridge by using real weekly asks as test cases.
Collaborate with preference-data engineers and post-training engineers to turn constraints and judgment into signals that models can learn from.