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Npu Jobs in Texas (NOW HIRING)

The role will deliver improved GPU/NPU utilization for AI workloads. The role offers tangible feedback to enhance product quality, while overseeing tracking and reporting of product-related ...

AI/ML Logic Design Engineer-Senior

Austin, TX · On-site

$127.20 - $190.80/hr

Overview Qualcomm Technologies, Inc. is seeking a design-focused engineer to contribute to the next generation of microarchitecture and logic for the Hexagon NPU, supporting a wide range of AI/ML ...

Design and development of next-generation microarchitecture and logic for Qualcomm's state-of-the-art Hexagon NPU, powering a wide range of AI/ML applications. In addition to microarchitecture and ...

Design and development of next‑generation microarchitecture and logic for Qualcomm's state‑of‑the‑art Hexagon NPU, powering a wide range of AI/ML applications. In addition to ...

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Npu information

See Texas salary details

$10

$25

$42

How much do npu jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for npu in Texas is $25.79, according to ZipRecruiter salary data. Most workers in this role earn between $17.93 and $27.31 per hour, depending on experience, location, and employer.

What is an NPU?

NPUs, or Neural Processing Units, are specialized hardware accelerators designed to efficiently handle artificial intelligence and machine learning tasks, particularly those involving neural networks. They are optimized for parallel processing and high-speed computation, making them much faster than traditional CPUs or GPUs for specific AI workloads. NPUs are commonly used in smartphones, data centers, and edge devices to process tasks like image recognition and natural language processing. Leveraging NPUs can significantly improve the performance and energy efficiency of AI applications.

What are the key skills and qualifications needed to thrive as an NPU engineer, and why are they important?

To thrive as an NPU Engineer, you need a strong background in computer engineering, digital signal processing, and deep learning algorithms, typically supported by a relevant degree in electrical engineering, computer science, or a related field. Familiarity with hardware description languages (such as Verilog or VHDL), AI frameworks (like TensorFlow or PyTorch), and experience with embedded systems or ASIC/FPGA design are essential. Problem-solving abilities, teamwork, and adaptability are critical soft skills for efficiently developing and optimizing NPU architectures. These skills ensure the design and deployment of high-performance, energy-efficient neural processing solutions for AI-driven applications.

How does an NPU engineer typically collaborate with software development teams during product development?

NPU engineers often work closely with software development teams to ensure that neural network models are optimized for deployment on specialized hardware. This collaboration includes profiling and quantizing models, identifying performance bottlenecks, and adjusting algorithms to maximize hardware efficiency. Regular communication is key, as engineers may need to translate high-level software requirements into hardware-accelerated solutions and provide feedback on model compatibility. Such teamwork ensures the final product delivers both speed and accuracy, bridging the gap between hardware capabilities and software demands.

What is the difference between Npu vs Network Planning Engineer?

AspectNpuNetwork Planning Engineer
Required CredentialsTypically a degree in telecommunications, electronics, or related field; certifications like CCNA or CCNPSimilar degrees; certifications like CCNA, CCNP, or equivalent
Work EnvironmentTelecom companies, network providers, data centersTelecom firms, ISPs, network service providers
Employer & Industry UsageDesigns and manages network hardware and infrastructurePlans, designs, and optimizes network layouts and capacity

Both roles require similar technical credentials and work in the telecommunications industry. While Npu focuses more on hardware and network infrastructure management, Network Planning Engineers concentrate on designing and optimizing network layouts. They often collaborate but serve different functions within network development and maintenance.

What are popular job titles related to Npu jobs in Texas?

For Npu jobs in Texas, the most frequently searched job titles are:

Infographic showing various Npu job openings in Texas as of August 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 86% Physical, 6% Hybrid, and 8% Remote job distribution, with an average salary of $53,648 per year, or $25.8 per hour.

Principal Engineer, NPU Architect

Renesas Electronics

Austin, TX

Full-time

Re-posted 10 days ago


Job description

Job Description

We are looking for a Principal NPU Hardware Architect with 10 to 15 years of experience to drive the architectural definition and hardware implementation of high-performance Neural Processing Units (NPUs) targeted for microcontrollers and microprocessors addressing Automotive high performance compute. This is a hardware-oriented role that requires a deep understanding of the full silicon lifecycle, combined with a strong background in hardware-software co-design to ensure the NPU architecture is highly optimized for compiler-driven execution and software stacks.

Responsibilities:

  • NPU Architecture & Dataflow: Define and own the end-to-end NPU micro-architecture, including high-throughput tensor/matrix engines, vector units, and specialized activation functional units.
  • Hardware-Software Co-Design: Partner closely with compiler and software teams to define instruction sets (ISA), memory management schemes, and hardware-aware graph optimizations.
  • Virtualization & Multi-Tenancy: Architect hardware-assisted virtualization features to enable secure resource sharing and multi-tenant execution in cloud or edge environments.
  • Interconnect & Fabric: Design and integrate high-bandwidth Bus fabrics (e.g., NoC, CHI) and DMA controllers optimized for the massive data movement inherent in AI workloads.
  • Infrastructure & Power: Lead the definition of SoC infrastructure elements, including complex clock/reset domains and advanced power management strategies to maximize performance-per-watt.
  • Performance Modeling: Develop bit-accurate and cycle-accurate C++/SystemC models to validate architectural choices and enable early software development.
  • Full Design Flow: Oversee the transition from architectural spec to RTL, providing technical leadership through verification, physical design, and post-silicon bring-up.
Qualifications
  • Education: Bachelor's or Master's in Electrical Engineering or Computer Engineering (PhD desirable)
  • Experience: 12+ years in AI accelerator, NPU, or GPU hardware architecture and RTL design.
  • Domain Expertise: Deep knowledge of deep learning primitives (CNNs, Transformers, RNNs) and how they map to spatial compute hardware.
  • Software Awareness: Strong understanding of compiler backends (e.g., LLVM, MLIR), IR transformations, and how hardware features like scratchpad memories or tiling impact compiler efficiency.
  • System Integration: Proven track record with modern SoC protocols (AXI/ACE/CHI) and integrating NPU cores into larger system-on-chip environments.
  • Modeling Skills: Expert-level proficiency in SystemC/TLM or C++ for architectural performance modeling and hardware-software co-verification.
  • Leadership: Ability to act as a technical authority, mentoring junior designers and influencing cross-functional roadmaps.
Additional Information

Renesas is an embedded semiconductor solution provider driven by its Purpose 'To Make Our Lives Easier.' As the industry's leading expert in embedded processing with unmatched quality and system-level know-how, we have evolved to provide scalable and comprehensive semiconductor solutions for automotive, industrial, infrastructure, and IoT industries based on the broadest product portfolio, including High Performance Computing, Embedded Processing, Analog & Connectivity, and Power.
With a diverse team of over 22,000 professionals in more than 30 countries, we continue to expand our boundaries to offer enhanced user experiences through digitalization and usher into a new era of innovation. We design and develop sustainable, power-efficient solutions today that help people and communities thrive tomorrow, 'To Make Our Lives Easier.'     
At Renesas, you can: 

  • Launch and advance your career in technical and business roles across four Product Groups and various corporate functions. You will have the opportunities to explore our hardware and software capabilities and try new things.  
  • Make a real impact by developing innovative products and solutions to meet our global customers' evolving needs and help make people's lives easier, safe and secure. 
  • Maximize your performance and wellbeing in our flexible and inclusive work environment. Our people-first culture and global support system, including the remote work option and Employee Resource Groups, will help you excel from the first day.    

Are you ready to own your success and make your mark?  

Join Renesas. Shape Your Future with Us.  

Renesas Electronics is an equal opportunity and affirmative action employer, committed to celebrating diversity and fostering a work environment free of discrimination on the basis of sex, race, religion, national origin, gender, gender identity, gender expression, age, sexual orientation, military status, veteran status, or any other basis protected by federal, state or local law. For more information, please read our Diversity & Inclusion Statement.

Renesas Electronics deals with dual-use technology that is subject to U.S. export controls regulations. Under these regulations it may be necessary for Renesas to obtain U.S. government export license prior to release of technology to certain persons. The decision whether or not to file or pursue an export license application is at the sole discretion of Renesas.

We have adopted a hybrid model that gives employees the ability to work remotely two days a week while ensuring that we come together as a team in the office the rest of the time. The designated in-office days are Tuesday through Thursday for innovation, collaboration and continuous learning.