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Samsung

Staff Emulation Engineer

San Jose, California, United States; SSI San Jose United States
Staff · AGI Computing Lab
POSTED 19 AUGVERIFIED 5H AGO
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Pay · posted
$219k–351k
mkt median $240k
Open for
77d
since 19 Aug
Hiring · 30d
74
+4 net · open roles

Please Note:

To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6-month period.

Advancing the World’s Technology Together

Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you’ll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what’s possible and powering the future.

We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We’re dedicated to empowering people to be their true selves. Together, we’re building a better tomorrow for our employees, customers, partners, and communities.

Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you’ll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what’s possible and powering the future.

We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We’re dedicated to empowering people to be their true selves. Together, we’re building a better tomorrow for our employees, customers, partners, and communities.

The AGI (Artificial General Intelligence) Computing Lab is dedicated to solving the complex system-level challenges posed by the growing demands of future AI/ML workloads. Our team is committed to designing and developing scalable platforms that can effectively handle the computational and memory requirements of these workloads while minimizing energy consumption and maximizing performance. To achieve this goal, we collaborate closely with both hardware and software engineers to identify and address the unique challenges posed by AI/ML workloads and to explore new computing abstractions that can provide a better balance between the hardware and software components of our systems. Additionally, we continuously conduct research and development in emerging technologies and trends across memory, computing, interconnect, and AI/ML, ensuring that our platforms are always equipped to handle the most demanding workloads of the future. By working together as a dedicated and passionate team, we aim to revolutionize the way AI/ML applications are deployed and executed, ultimately contributing to the advancement of AGI in an affordable and sustainable manner. Join us in our passion to shape the future of computing!

Location: Daily onsite presence at our San Jose, CA office / U.S. headquarters in alignment with our Flexible Work policy.

What You’ll Do

  • Build, bring up, and maintain large-scale hardware emulation and FPGA prototyping platforms for memory-centric computing SoCs, enabling pre-silicon hardware and software validation.
  • Partition and map complex multi-million-gate designs onto emulation systems and multi-FPGA prototypes, optimizing for capacity, run-time performance, and debug visibility.
  • Develop transactors, speed bridges, and co-emulation (SCE-MI) environments that connect the design under test to host software and virtual or physical interfaces.
  • Model memory subsystems, clock and reset schemes, and high-speed I/O interfaces for accurate, high-throughput emulation and prototyping.
  • Enable early firmware, driver, and software bring-up by delivering stable emulation and prototype targets with robust debug infrastructure.
  • Run AI/ML workloads and performance benchmarks pre-silicon to validate functionality and system-level performance.
  • Debug complex hardware and software issues using waveform capture, assertions, and coverage, driving root-cause analysis together with design, verification, and software teams.
  • Make trade-offs between emulation and prototyping — capacity, speed, bring-up time, and debug — to select the right platform for each project milestone.
  • Develop and automate emulation and prototyping flows (compile, partitioning, and build) using scripting and agentic AI tools and frameworks to improve turnaround time and quality of results.
Source · SamsungFirst seen 2 NovOriginal ↗