Research Software Engineer- Simulation Algorithm/ Geometry Processing

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REQUIRED: MUST have experience with Code Development + Computational Design and/or Geometry Processing. Applicants will not be considered without this experience. About Us: We are an MIT-born, venture-backed Silicon Valley startup building a real-life 'Jarvis'. An AI Copilot for design and manufacturing. Our goal is to utilize advanced AI, physics simulation, and computer graphics to reduce costs and improve engineering productivity across all steps of the design and manufacturing process. On this Role: This role is a mix of a few worlds coming together. You’ll be working with machine learning but not in a vacuum. It’s applied to real engineering problems, working with 2D and 3D data from CAD, CAE and CAM systems. A big part of the work is taking complex geometry, design workflows and simulation data and figuring out how to turn that into something an AI system can actually understand and use. We’re looking for someone who’s strong technically, especially in Python and ML but also has the curiosity to dig into how things are designed and built in the real world. You might come from a research background or industry but either way you’re comfortable moving between theory and practical application. If you’ve spent time around mechanical systems or engineering design, that’s a big plus because a lot of this role is about bridging that gap between advanced models and how engineers actually work day to day. Responsibilities Design, develop, and maintain geometry processing and simulation algorithms for engineering applications. Build services for reading, processing, and writing 2D/3D engineering data. Develop rendering modules for generating 2D/3D visual assets. Curate and manage large-scale datasets for learning-based systems. Implement and optimize post-training workflows for machine learning models. Contribute to the development of domain-specific languages for engineering tasks. What we are looking for 5+ years of academic or industry experience in one or more of the following areas: Geometric Processing, Simulation, Optimization, Machine Learning, or Domain-Specific Languages. Proficient in writing clean, modular, and maintainable Python code. Experience with dataset creation and data pipeline development. PhD or MS with a focus in Computational Design, Simulation, or AI. Experience developing CAD/CAM/CAE software tools. Experience developing or fine-tuning large language models (LLMs), including post-training methods such as quantization, pruning, distillation, or reinforcement learning. Experience designing or implementing DSLs or compilers. Originally posted on Himalayas

必需：必须具备代码开发 + 计算设计和/或几何处理的经验。不具备此经验的申请者将不予考虑。关于我们：我们是一家诞生于MIT、由风险投资支持的硅谷初创公司，正在打造现实生活中的“Jarvis”。一款用于设计和制造的AI Copilot。我们的目标是利用先进的AI、物理仿真和计算机图形学，降低设计及制造全流程的成本并提升工程生产力。关于此职位：这个角色是多个领域的交汇。你将与机器学习打交道，但并非孤立地进行。它将应用于真实的工程问题，处理来自CAD、CAE和CAM系统的2D和3D数据。工作的很大一部分是处理复杂的几何形状、设计工作流和仿真数据，并弄清楚如何将其转化为AI系统真正能够理解和使用的东西。我们在寻找技术能力强的人，尤其是在Python和ML方面，但同时也要有好奇心去深入研究现实世界中事物是如何设计和建造的。你可能来自研究背景或工业界，但无论哪种，你都能在理论与实践应用之间自如切换。如果你曾接触过机械系统或工程设计，那将是一个很大的加分项，因为这个角色的很多工作就是在先进模型与工程师日常工作方式之间架起桥梁。职责：为工程应用设计、开发和维护几何处理与仿真算法。构建用于读取、处理和写入2D/3D工程数据的服务。开发用于生成2D/3D视觉资产的渲染模块。策划和管理面向学习型系统的大规模数据集。实现并优化机器学习模型的训练后工作流。为工程任务的领域特定语言开发做出贡献。我们期望的人选：在以下一个或多个领域拥有5年以上的学术或工业经验：几何处理、仿真、优化、机器学习或领域特定语言。精通编写整洁、模块化且可维护的Python代码。具有数据集创建和数据流水线开发的经验。拥有计算设计、仿真或AI方向的博士或硕士学位。具有开发CAD/CAM/CAE软件工具的经验。具有开发或微调大型语言模型（LLMs）的经验，包括量化、剪枝、蒸馏或强化学习等训练后方法。具有设计或实现DSL或编译器的经验。原发布于Himalayas

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