Custom Automation CAD Engineer

Summary

Posted: Nov 19, 2024

Role Number:200579318

Interested in how Apple designs the world’s most advanced silicon? Want to write software that helps create the next generation of processors and enables the next astonishing Apple innovation? There's no telling what you could accomplish at Apple! We’re looking for an engineer who will bring passion for hardware and strong programming skills to our team of CAD engineers. You’ll gain hands-on experience in the application of machine learning to circuit design automation and the reuse of custom IP. You’ll develop innovative pipelines to enable design engineers to efficiently drive and interact with their transistor-level analysis workflows, delivering diverse IPs targeted for our many ICs in development. In this role, you will have the opportunity to acquire a broad spectrum of knowledge spanning various disciplines and stages of silicon IP development, including, but not limited to, applications in machine learning (ML) and large language modeling (LLM) technologies and the enablement of reusable IPs. These LLM applications encompass tasks such as information retrieval, triage, and chatbot development, alongside traditional silicon design areas such as transistor-level extraction, timing analysis, static/dynamic IR analysis, simulations, power EM analysis, signal EM analysis, logic equivalency checks (LEC), and signoff. The successful candidate will excel in dynamic, collaborative working environments and exhibit a hands-on, enthusiastic, self-motivated approach, with a strong drive to succeed in challenging settings. If you are eager to tackle challenges with innovative solutions, deliver exceptional user experiences, and pay meticulous attention to detail, this role may be the perfect fit for you. As a member of our team, your contributions will directly impact the experiences of millions of Apple customers in delivering state of the art processors to the wide range of Apple products.

Description

In this highly visible role, your primary responsibilities will include: - Developing innovative ML and large language model applications to understand, explain, and interact with advanced circuit design software systems. Designing and implementing their interaction with our extensive compute infrastructure. - Identifying opportunities for optimizing, expediting, and reusing the delivery of hardware IP assets. - Actively involving yourself in supporting various ML and large language model development processes, including understanding input data, troubleshooting output, resolving software challenges that may impact project timelines, and delivering solutions to our internal customers. - Closely collaborating with diverse design teams, including Custom Digital, Analog, Mixed-Signal, and more, to understand their needs and requirements for various ML and large language model applications. Applying advanced techniques to address these requirements across multiple products and reduce duplicate design work. - Working in tandem with other experts in CAD to validate their ML-based applications, implement enhancements, and evaluate external vendor packages and solutions from EDA (Electronic Design Automation) providers and open-source.

Minimum Qualifications

• Experience in developing object-oriented programs, utilizing data structures, and writing algorithms
• Experience in writing machine learning algorithms, implementing natural language processing (NLP), or using large language models in industry applications
• Experience with transistor-level electrical engineering and related software tools for circuit analysis, such as simulation, timing, EM/IR, layout, extraction, or power analysis
• Day-to-day experience working with the UNIX shell environment and code revision control systems
• Experience leading industry electrical engineering-focused software development projects
• Minimum requirement of BS degree and 10+ years of relevant industry experience

Preferred Qualifications

• Experience in electrical engineering machine learning applications
• Experience with large language models, including fine-tuning, retrieval augmented generation, and prompt engineering
• Experience with server management, and parallel computing platforms such as LSF, NC, AWS, etc.