Computational Engineer Jobs in Virginia (NOW HIRING)

ABOUT US

Hey! We’re Molg 👋 We’re building robotic systems that make electronics manufacturing circular. We work with hyperscalers and leading electronics manufacturers to automate how hardware is designed, manufactured, disassembled, repaired, reused, and recovered. Using robotics, computational design, and AI, our systems turn today’s e-waste into resilient, data-driven supply chains—and change how electronics are made in the first place.

A core part of what makes Molg's systems work is spatial intelligence: the ability to understand, model, and reason about complex physical environments—down to the geometry, tolerances, and dynamics of individual components. Our synthesis and computational design platform sits at the intersection of geometry, algorithms, and physical reasoning, and is central to how we automate the design and execution of manufacturing and disassembly processes at scale.

IN THIS ROLE YOU WILL:

Join a talented cross-functional team of robotics, software, mechanical, and electrical engineers to develop Molg's computational design and spatial intelligence platform. As a Synthesis / Computational Design Engineer, you will:

• Design and implement algorithms for geometric reasoning, spatial analysis, and computational synthesis—enabling Molg's systems to automatically understand and operate on complex physical assemblies.

• Build the computational backbone for automated process planning: translating 3D representations of electronics into actionable, robot-executable sequences for assembly, disassembly, repair, and recovery.

• Develop tools and pipelines for working with 3D geometry—including mesh processing, point cloud analysis, CAD interoperability, and physics-informed simulation—to support perception, planning, and verification workflows.

• Collaborate with robotics and controls engineers to close the loop between spatial models and physical execution—ensuring that synthesized plans are feasible, robust, and safe.

• Contribute to the design and evolution of Molg's internal data models for representing products, components, processes, and spatial relationships across the manufacturing lifecycle.

• Prototype and evaluate new approaches to geometric search, constraint solving, and design space exploration—drawing from fields like computational geometry, CAD/CAM, and generative design.

• Build scalable, production-grade software that integrates computational design capabilities into Molg's broader robotics and microfactory platform.

• Participate in design reviews and technical discussions, bringing rigorous geometric and algorithmic thinking to cross-functional problems.

• Stay current with advances in computational design, geometry processing, and spatial AI—identifying and applying relevant techniques to Molg's challenges.

You'll have the opportunity to build alongside an incredible team, develop innovative solutions, and grow in a fast-paced environment that values autonomy and impact.

WHO YOU ARE:

We're looking for someone who combines strong algorithmic and geometric instincts with the engineering rigor to build reliable, production-quality systems. The ideal candidate has:

• 5+ years of experience in computational geometry, geometric computing, computational design, CAD/CAM software development, or a closely related field.

• Proficiency in Python and/or C++, with experience writing performance-sensitive geometric or numerical code.

• Deep familiarity with 3D geometry representations—meshes, point clouds, solid models (B-rep), voxel grids, or implicit surfaces—and the algorithms that operate on them.

• Experience with one or more geometry processing or computational design tools or libraries (e.g., Open3D, CGAL, libigl, OpenCASCADE, Rhino/Grasshopper, or similar).

• Strong understanding of linear algebra, computational geometry fundamentals, and numerical methods as applied to 3D problems.

• Comfort working in a research-to-production context: able to prototype rapidly, then harden and scale solutions for real-world deployment.

• Experience integrating geometric pipelines with downstream systems—robotics, simulation, databases, or web services.

• A track record of shipping complex technical work end-to-end, not just prototyping.

• Excellent communication skills; able to explain geometric and algorithmic concepts clearly to engineers from different disciplines.

Nice to have:

• Experience with robotic motion planning, task planning, or manipulation—particularly in the context of geometric reasoning.

• Familiarity with machine learning approaches to geometry (e.g., 3D neural representations, learned shape descriptors, or spatial transformers).

• Background in electronics manufacturing, PCB design, or physical product development.

• Experience with physics simulation (e.g., PyBullet, MuJoCo, Isaac Sim) or tolerance analysis.

• Contributions to open-source geometry or robotics software.

WHO WE ARE:

We spend our days building robotic systems, developing complex assembly intelligence software, and designing the next generation of circular products for our customers. Given the importance of working hands-on with physical systems, the majority of our team is in-person collaboratively working in our industrial space in Sterling, VA, down the road from the largest data center market in the world. Our facility includes a variety of robots, CNC milling machines, 3D printers, and all the tools needed to build and test our products. It is important to us that anyone on our team that is interested in learning how to use our various pieces of equipment and machinery is taught and can gain the skills and appreciation for making physical things.

THINGS TO KNOW:

• We’re a hands on collaborative team with big ambitions, and there’s a good amount of context-switching. We expect people to be autonomous and drive their own work to completion.

• We are scrappy and looking to build a great sustainable company for years to come.

• As a growing company and startup, priorities may shift as customer or business requirements change. We strive to empower individuals with context and decision-making power to meet this need.