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Senior Staff Engineer, GPU Architect, Machine Learning
3655 N 1st St, San Jose, CA, USA
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hirly's read of this role
- Role family
- Engineering
- Seniority
- Lead / management
- Stated salary
- $198,200 per year
- Country
- US
- Work mode
- On-site / unstated
- First seen by hirly
- 27 Sept 2026
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the posting
Position Summary
Samsung, a world leader in advanced semiconductor technology, is founded on a simple philosophy – the endless pursuit of excellence will create a better world for all. At Samsung Austin Research and Development Center (SARC) and Advanced Computing Lab (ACL), we are building a center of excellence for Intellectual Property (IP) that is applied to high-performance computing devices (mobile, automotive, and other custom market segments) consumed by millions of people around the world. Come build with us!
Role and Responsibilities
As a Senior Staff GPU Architect – Machine Learning, you will help lead the design and development of innovative machine learning (ML) solutions for Samsung’s premium mobile GPUs.
In this high-impact individual contributor role, you will drive architectural innovation at the intersection of GPU and machine learning design to enable efficient execution of large-scale AI models. You will collaborate across hardware, software, and research teams to define new GPU features, analyze workloads, and deliver architectures that advance performance, power efficiency, and scalability for next-generation intelligent computing.
- You are passionate about architecting and defining ML-driven hardware features and extensions that integrate seamlessly with the graphics pipeline, advancing GPU performance, power, and functionality for AI workloads.
- You enjoy learning about analyzing and modeling representative ML workloads to identify bottlenecks, uncover optimization opportunities, and guide architectural trade-offs that maximize PPA on applications such as LLMs, LVMs, and image classification.
- You support design excellence by working on improving middleware and hardware-software integration to optimize GPU architectures for ML workloads—ensuring maximum performance and power efficiency.
- You proactively seek cross-functional collaboration with GPU architects, RTL and software engineers, and research teams, to translate ML insights into production-ready GPU designs and influence long-term AI architecture roadmap.
You take initiatives on moderate-to-complex projects and help advance best practices, methodologies by staying ahead of industry trends and emerging technologies.
Skills and Qualifications
- 11+ years of experience with a Bachelor's degree in Computer Science/Computer Engineering/relevant technical field, or 9+ years of experience with a Master's degree, or 7+ years of experience with a PhD.
- Knowledge of machine learning principles and architectures
- Knowledge of computer vision algorithms, AR/VR, and Ray Tracing
- Knowledge of computer architectures and performance optimization
- Experience with workload analysis and modeling
- Strong programming skills in languages such as C++, Python, or similar
- Familiarity with LLMs, LVMs, and image classification
- Experience with GPU architecture and graphics pipeline
- Knowledge of ML frameworks and tools (e.g., TensorFlow, PyTorch)
- Ability to write clear and concise technical specifications
- Strong analytical and problem-solving skills, with the ability to identify bottlenecks and propose data-driven solutions
- Excellent communication and collaboration skills, with the ability to navigate ambiguity in a fast-paced, global team environment
Our Team
The GPU Architect team delivers whole system architecture-level design for Samsung’s current and next-generation mobile GPUs. Our work spans a wide range of disciplines—from early-stage architectural exploration and research in graphics and machine learning, to shaping the GPU innovation roadmap, defining new features, building models, and delivering microarchitecture design and programming. Our Xclipse GPU is the first mobile GPU with ray tracing technology that enables console-level graphics for Samsung Galaxy smartphones.
Joining our team means collaborating with talented engineers from diverse technical backgrounds across a global organization. Here you’ll contribute to the roadmap for next-generation technologies, broaden your expertise, and solve impactful challenges in a supportive environment that values collaboration, continuous learning, and growth.
Total Rewards
At Samsung – SARC/ACL, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $198,200 and $297,200. Your actual base pay will depend on variables that may include your education skills, qualifications, experience, and work location.
Samsung employees have access to benefits including: medical, dental, vision, life insurance, 401(k), onsite lunch, employee purchase program, tuition assistance (after 6 months), paid time off, student loan program, wellness incentives, and many more. In addition, regular full-time employees (salaried or hourly) are eligible for MBO bonus compensation, based on company, division, and individual performance.
Additionally, this role might be eligible to participate in long term incentive plan and relocation.
This is an exempt position, which is not eligible for overtime pay under the Fair Labor Standards Act (FLSA).
Trade Secrets
By submitting an application, you agree not to disclose to Samsung or induce or encourage Samsung to use any confidential or proprietary information (including trade secrets) belonging to a current or former employer or other entity.
U.S. Export Control
This role may require access to information subject to U.S. export control laws. Applicants must be authorized to access such information or eligible for government authorization.
#SARC #ACL
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* Samsung Electronics America, Inc. and its subsidiaries are committed to employing a diverse workforce, and provide Equal Employment Opportunity for all individuals regardless of race, color, religion, gender, age, national origin, marital status, sexual orientation, gender identity, status as a protected veteran, genetic information, status as a qualified individual with a disability, or any other characteristic protected by law.
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