GPU AI Compute Architect

Job Details:

Job Description: 

We are seeking a highly skilled GPU Compute Architect with a strong background in microarchitecture (uArch) and Register-Transfer Level (RTL) design to join our team. This individual will play a critical role in prototyping and designing advanced compute arithmetic components such as MAC (Multiply-Accumulate) arrays and ALUs (Arithmetic Logic Units) for GPUs tailored to AI applications, with a focus on delivering comprehensive power and area estimates for each design option.

Key Responsibilities:

• Design and prototype advanced compute arithmetic units (e.g., MAC arrays, ALUs) for GPUs targeting AI and deep learning workloads.

• Develop and optimize GPU microarchitectures to enhance performance, energy efficiency, and scalability for AI-specific applications.

• Create and refine RTL implementations to validate and benchmark new design concepts.

• Conduct detailed performance modelling and analysis to identify bottlenecks and propose innovative solutions for next-generation GPU designs.

• Produce comprehensive power and area estimates for proposed designs, enabling informed trade-off analysis and decision-making.

• Collaborate with cross-functional teams, including software, hardware, and machine learning experts, to align architecture design with application requirements.

• Research and integrate emerging technologies and methodologies in GPU compute design for AI workloads.

• Lead the evaluation of design trade-offs in terms of performance, area, and power metrics.

• Drive innovation in custom compute unit design, ensuring compatibility with broader GPU pipeline architecture.

Qualifications:

Required:

• Master's or Ph.D. in Electrical Engineering, Computer Engineering, Computer Science, or a related field.

• Proven related experience in GPU/ASIC architecture design, with a focus on compute arithmetic via course work or relevant projects.

• Expertise in microarchitecture design and RTL coding (e.g., SystemVerilog).Strong understanding of GPU pipelines, parallel computing concepts, and AI/ML workloads.

• Proven experience in designing and optimizing MAC arrays, ALUs, or similar compute units.

• Solid knowledge of hardware modelling and simulation tools (e.g., VCS, Synopsys, ModelSim).Experience in producing and interpreting power and area estimates for complex hardware designs.

• Proficiency in performance analysis tools and techniques.

• Strong problem-solving skills with the ability to innovate and think out of the box.

Preferred:

• Familiarity with high-level synthesis (HLS) tools and methodologies.

• Background in machine learning algorithms and their hardware acceleration.

• Understanding of power optimization techniques and methodologies for compute-intensive hardware.

• Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.

          

Job Type:

Experienced Hire

Shift:

Shift 1 (Ireland)

Primary Location: 

Ireland, Leixlip

Additional Locations:

Business group:

The Client Computing Group (CCG) is responsible for driving business strategy and product development for Intel's PC products and platforms, spanning form factors such as notebooks, desktops, 2 in 1s, all in ones. Working with our partners across the industry, we intend to deliver purposeful computing experiences that unlock people's potential - allowing each person use our products to focus, create and connect in ways that matter most to them. As the largest business unit at Intel, CCG is investing more heavily in the PC, ramping its capabilities even more aggressively, and designing the PC experience even more deliberately, including delivering a predictable cadence of leadership products. As a result, we are able to fuel innovation across Intel, providing an important source of IP and scale, as well as help the company deliver on its purpose of enriching the lives of every person on earth.

Posting Statement:

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

Position of Trust

N/A

Work Model for this Role

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.