$76,900 - $120,100 USD yearly
Originally posted 24 September 2026 by the employer.
Validate and optimize NPU silicon solutions.
About the role
As a Sr Deep Learning Hardware Verification Engineer, you will validate and optimize NPU silicon solutions. Your contributions will directly shape Intel's advancements in AI technologies.
What you'll do
- Perform Functional Verification of complex digital design block(s) on Intel's NPU AI accelerators.
- Architect, develop, and implement verification environments from initial planning through validation lifecycle to review and signoff.
- Develop test plans and test cases.
- Implement random test generators, high-level transactional models, bus functional models (BFMs), functional/formal constraints, checkers and scoreboards, coverpoints/covergroups, and SVA properties.
- Implement software-based test cases for functional and performance-based testing of the NPU AI accelerators.
- Collaborate with cross-functional teams to analyze and address AI requirements, influencing the AI product roadmap.
What you'll need
- Bachelor's degree in Electronic, Computer Engineering, Computer Science or a related field.
- 8+ years of relevant industry experience in pre-silicon validation of IP's, ASIC, SoC, or FPGA designs.
- Proficiency with industry standard verification tools and methodologies (System Verilog, VCS, UVM, OVM).
- Expertise in developing testbenches, test plans, and functional/formal verification environments.
- Proven track record of signing off complex designs through coverage closure and related techniques.
Nice to have
- Experience with C-based Software driver development and testing.
- Experience with validating low power and high performance designs, HW accelerators.
- Proficiency in System Verilog Assertions.
- Experience with formal verification techniques and tools.
- Knowledge of Git and Continuous Integration (CI) practices.
- Established knowledge of SoC based CPUs, NoCs, AMBA protocols, and memory controllers.
- Understanding of deep learning techniques and experience working with frameworks such as TensorFlow, PyTorch, or OpenCV.
Skills: NPU silicon solutions, AI accelerators, Functional Verification, System Verilog, UVM
This role has been open 2 days — well below the 68-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
509
|
Median days open
68 d
|
Median salary
$225k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Intel Corporation | All employers we track in this specialty (509 roles · 75 employers) |
|---|---|---|
| Open roles in this specialty | 10 | 509 |
| Open roles in the wider Software, Firmware & Systems family | 155 | 5833 · 143 employers |
| Median days open | 24 d | 68 d (−44 d vs this employer) |
| Median salary (USD postings) | — | $225k |
Skills observed across this category: NPU silicon solutions, AI accelerators, Functional Verification, System Verilog, UVM
Who's hiring in this category
- Qualcomm · 105 open roles · median 102 d
- NVIDIA · 81 open roles · median 65 d
- AMD · 46 open roles · median 61 d
- Micron Technology · 32 open roles · median 45 d
- Mobileye · 21 open roles · median 61 d
- Analog Devices · 14 open roles · median 30 d
How we counted: 509 open AI/ML Hardware Engineering (AI ML Hardware) roles from 75 employers tracked in the SemiconductorJobs index, counted 27 Sept 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.