Introduction
We're looking for a Machine Learning Engineer to help revolutionize the semiconductor design process. This role focuses on leveraging AI to build products used in high-impact, real-world scenarios. If you're passionate about building robust, production-level systems that push technological boundaries, this opportunity might be for you.
About the Company
Our company operates at the forefront of semiconductor innovation, addressing bottlenecks in chip design by applying advanced AI techniques. With deep experience in optimizing power, performance, and area (PPA), we're leading the way in transforming how the world designs chips. The challenges we solve impact datacenters, AI, and edge computing globally.
About the Role
As a Machine Learning Engineer, you'll be responsible for developing scalable ML systems that will be integral to the chip design process. You will work on end-to-end machine learning pipelines, including dataset creation, data pipeline development, and fine-tuning both open-source and closed-source large language models (LLMs) like GPT and Claude. The focus will be on building application layers that produce actionable insights and outputs for chip designers.
What We Can Offer You:
- Competitive salary
- Equity options
- Work on cutting-edge technology with real-world impact
- Flexible working environment
- Access to industry-leading tools and experts
- A chance to influence the future of semiconductor design
Key Responsibilities:
- Develop and maintain scalable ML pipelines from data collection to production
- Fine-tune large language models (LLMs) for performance in specialized chip design tasks
- Build agentic workflows to automate tasks and enhance productivity
- Collaborate with teams to create applications that translate ML outputs into practical design optimizations
- Ensure systems meet the speed, accuracy, and quality requirements needed in high-volume production environments
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