高级机器学习工程师
Senior ML Engineer
关于 Quilter
在 Quilter，我们通过自动化设计印刷电路板（PCB）的繁琐和耗时任务，帮助电子工程师节省时间并完成更多工作。我们的小团队由电子工程、电磁仿真、ML/AI 和高性能计算（HPC）领域的专家组成。我们正在发明和利用新技术，解决几十年来自动化电路板设计的问题，而目前每年在这方面的投入高达数千亿美元。我们从一些最优秀的投资方获得了 2500 万美元的 B 轮融资，并正全速向目标迈进。
无论我们来自哪里，我们都因共同的未来愿景和一套我们认为能带我们到达彼岸的核心价值观而团结在一起：
- 专注于使命
- 打造有助于人类的伟大产品
- 展现坚韧不拔的精神
- 持续学习
- 追求卓越
我们正在寻找一位高级 ML 工程师加入 Quilter 的 Placer 团队，帮助我们构建自动化 PCB 元件布局的 AI。
职位描述
Placer 负责 PCB 的自动元件布局。该角色涵盖整个生命周期：研究、原型开发、生产化和维护。你将在一个困难且现实的组合问题上，跨优化、机器学习和几何深度学习进行工作。
这是一个完全分布式团队。我们期望你具备高度的自主性和所有权意识。
你将负责
- 从探索性研发到生产就绪、可维护的系统，全程负责问题
- 开发和扩展使用 PyTorch 和 CUDA C++ 的 GPU 加速代码
- 在包括强化学习、图神经网络、黑盒/经典优化和生成建模在内的广泛建模领域中工作
- 制定目标、模型约束，并调试堆栈中的数值行为
- 与高级队友一起贡献技术方向和研究策略
我们寻找的人才
- 5 年以上 ML、优化或相关领域的行业经验
- 扎实的机器学习和优化基础
- PyTorch 生产环境经验
- 在研究和生产代码库之间工作的能力
- 在模糊的问题空间中独立操作的能力
- 良好的沟通和协作技能
优先考虑
- 5-7 年行业经验（可能考虑高级职位）
- CUDA C++ 经验
- 在以下任意组合背景中：强化学习、几何深度学习、图神经网络
查看英文原文
About Quilter
At Quilter, we are helping electrical engineers save time and accomplish more by automating the tedious and time-consuming task of designing printed circuit boards (PCBs). Our small team is composed of experts in electrical engineering, electromagnetic simulation, ML/AI, and high-performance computing (HPC). We are inventing and leveraging novel techniques to solve the decades-old problem of automating circuit board design where today hundreds of billions of dollars are spent. We have raised $25 million in Series B funding from some of the very best and are charging full-speed toward our goal.
No matter where we come from, we're united by a common vision for the future and a core set of values we think will get us there:
- Focus on the mission
- Build great things that help humans
- Demonstrate grit
- Never stop learning
- Pursue excellence
We're looking for a Senior ML Engineer to join Quilter's Placer Team and help us build the AI that automates component placement on PCBs.
The Role
The Placer is responsible for automated component placement on PCBs. This role spans the full lifecycle: research, prototyping, productionization, and maintenance. You'll work across optimization, machine learning, and geometric deep learning on a hard, real-world combinatorial problem.
This is a fully distributed team. We expect high autonomy and high ownership.
What Youʼll Do
- Own problems end-to-end from exploratory R&D through production-hardened, maintainable systems
- Develop and extend GPU-accelerated code in PyTorch and CUDA C++
- Work across a broad modeling landscape including RL, graph neural networks, black-box/classical optimization, and generative modeling
- Formulate objectives, model constraints, and debug numerical behavior in the stack
- Contribute to technical direction and research strategy alongside senior teammates
What Weʼre Looking For
- 5+ years of industry experience in ML, optimization, or a related field
- Strong fundamentals in machine learning and optimization
- Production PyTorch experience
- Demonstrated ability to work across research and production codebases
- Comfort operating with high autonomy in ambiguous problem spaces
- Strong communication and collaboration skills
Preferred
- 5–7 years of industry experience (Staff-level appointment may be considered)
- CUDA C++ experience
- Background in any combination of: reinforcement learning, geometric deep learning, graph neural networks, multi-objective optimization, combinatorial optimization
Please note: We are an equal opportunity employer. At this time, we are focused on hiring primarily within the US, with occasional exception to accommodate exceptional talent.
What we offer:
- Interesting and challenging work
- Competitive salary and equity benefits
- Health, dental, and vision insurance
- Regular team events and offsites (~4x / year)
- Unlimited paid time off
- Paid parental leave
Want to learn more about Quilter, our vision, and our investors? Visit our About page and visit our Blog.