Deep Learning Hardware Engineer

Job Description: 

The Role and Impact

Intel's Client AI Architecture team is seeking an Deep Learning Hardware Engineer to help shape future generations of Intel's Neural Processing Unit (NPU) architecture for AI PCs, Edge AI, Agentic AI, Physical AI, and multimodal foundation models.

In this role, you will work at the intersection of AI, computer architecture, and hardware-software co-design to optimize AI workloads and drive innovations in next-generation AI acceleration technologies. You will collaborate with architecture, software, compiler, and machine learning teams to develop high-performance, power-efficient AI solutions for Intel client platforms.

The ideal candidate has experience developing, optimizing, or deploying AI workloads on NPUs, GPUs, AI accelerators, or related computing architectures. Experience with Intel NPUs, OpenVINO, AI software stacks, compiler technologies, AI inference optimization, and hardware-software co-design is highly desirable.

What You’ll Do

Key responsibilities will include but not limited to:

• Contribute to the design and optimization of neural compute and AI accelerator architectures.
• Develop and evaluate RTL implementations of hardware features supporting machine learning workloads.
• Analyze AI models and workloads to identify performance, power, and efficiency opportunities.
• Partner with architecture, software, and algorithm teams to define future hardware capabilities.
• Support hardware-software co-design efforts to optimize AI solutions across the technology stack.
• Evaluate neural network mapping strategies for accelerated inference execution.
• Apply optimization techniques such as quantization, compression, pruning, and sparsity to improve AI efficiency.
• Utilize computer architecture principles including pipelining, parallelism, memory hierarchy, and data movement optimization.
• Participate in technical innovation activities, including invention disclosures, patents, conference papers, and publications.

Behavioral traits that we are looking for:

• Curiosity & Learning Agility – Eager to learn new technologies, quickly absorb concepts, and continuously develop technical expertise.
• Problem Solving – Uses analytical thinking to break down complex challenges and develop practical, data-driven solutions.
• Collaboration – Works effectively across diverse teams, values different perspectives, and builds strong working relationships.
• Ownership & Initiative – Takes responsibility for deliverables, follows through on commitments, and proactively identifies opportunities for improvement.
• Adaptability – Thrives in a fast-paced environment, embraces change, and adjusts priorities as business needs evolve.
• Communication – Clearly communicates technical concepts, ideas, and recommendations to both technical and non-technical audiences.
• Innovation Mindset – Demonstrates creativity, challenges assumptions, and seeks new approaches to improve products, processes, and customer outcomes.

Intel invests in our people and offers a complete and competitive package of benefits employees and their families through every stage of life. 

• See  Intel Benefits for more details. 

Qualifications:

You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.  Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.

Note:

For information on Intel’s immigration sponsorship guidelines, please see

Intel U.S. Immigration Sponsorship Information

Minimum Qualifications and Experience: 

Bachelor's degree in Computer Science, Electrical Engineering, or a STEM-related field with 3+ years of relevant experience; OR Master's degree in the same fields with 2+ years of experience; OR PhD degree in the same fields with 3+ months of educational or work experience.

Your experience described above must be in the following:

• Digital Logic Design and RTL Design using System Verilog or Verilog.
• AI model architectures, layers, activation functions, and neural network topologies (e.g., Llama, Qwen, DeepSeek, Pi0.5).
• Experience working with Git workflows and repositories.
• Optimizing AI models for performance, such as quantization, pruning, and compression.

 Preferred Qualifications and Experience:

• Familiarity with AI frameworks, neural computing operations, and hardware-accelerated inference techniques.
• Hands-on experience with modern deep learning topologies, including foundational models.
• In-depth knowledge of computer architecture concepts such as multi-core/multi-threading, memory hierarchy, and floating-point vs. fixed-point computations.
• Experience collaborating in cross-disciplinary teams to align hardware and software requirements.

Why Join Us

The Client Computing Group (CCG) develops industry-leading technologies that power personal computing experiences around the world. Within Intel's AI Hardware Engineering organization, you'll help build the neural compute technologies that drive future AI-enabled PCs and intelligent computing platforms.

 This role provides opportunities to:

• Work on cutting-edge AI and machine learning technologies.
• Learn from industry-leading hardware and AI experts.
• Influence next-generation AI silicon architecture.
• Collaborate across hardware, software, and research teams.

Job Type:

Shift:

Primary Location: 

Additional Locations:

Posting Statement:

Position of Trust

Benefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Work Model for this Role

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