Software Engineer, PhD, Early Career, Embedded Systems and Firmware
Listed on 2026-06-20
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Software Development
Software Engineer, Machine Learning/ ML Engineer
Software Engineer, PhD, Early Career, Embedded Systems and Firmware, 2026 Start
Google | Posted Mar 11 | Full-time | North Carolina | Entry (0-2 yrs)
Applicants in the County of Los Angeles:
Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
By applying to this position you will have an opportunity to share your preferred working location from the following:
Sunnyvale, CA, USA;
Atlanta, GA, USA;
Kirkland, WA, USA;
Los Angeles, CA, USA;
Mountain View, CA, USA;
New York, NY, USA;
Raleigh, NC, USA;
Durham, NC, USA;
Seattle, WA, USA
.
- PhD degree in Computer Science, or a related field, or equivalent practical experience.
- Experience in embedded systems/firmware design.
- Experience coding in C or C++.
- Knowledge of one or more of the following:
Microcontrollers, SoC, device drivers, hardware, power management, ARM processors, performance optimization, file systems, bootloading, firmware, x86 assembly, system BIOS, or hardware/software integration. - Knowledge of Unix/Linux environments and kernel development.
- Ability to start full-time role in 2026.
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large‑scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile;
the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast‑paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full‑stack as we continue to push technology forward.
As a PhD graduate, your research expertise is invaluable to us. Explore a variety of projects, collaborate with various teams, and contribute to products that are changing the world, across many product areas, including AI & Infrastructure, Cloud, and more!
Our Engineering teams include thousands of PhDs who bring their deep knowledge and research experience to enhance our systems and products. As a Google PhD Software Engineer, you will work on critical projects, with many opportunities to learn and follow your interests. We expect our engineers to be creative and versatile, leading and identifying new problems to push the field and Google technology forward.
Google is one of the world’s leading suppliers and consumers of ML and AI technology, with decades of experience in designing, deploying, and using ML software and custom ML hardware infrastructure at massive scale.
Responsibilities- Participate in or lead team projects to carry out design, analysis, and development of advanced systems across the stack, particularly embedded systems.
- Develop code and review code developed by other developers, and provide feedback to ensure best practices (e.g., style guidelines, accuracy, testability, and efficiency).
- Write documents that set new technical directions. Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Study, diagnose and resolve complex technical issues by analyzing the sources of the issues and the impact…
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