Senior Engineer - Computing Architecture (Italy-based)

The Senior Engineer - Computing Architecture at Axelera AI is responsible for defining and developing innovative computing architectures specifically tailored for AI systems. This includes performance optimization by analyzing computational workloads, driving innovation by evaluating emerging technologies, and collaborating closely with hardware and software teams to ensure the integration of performance, cost, and power efficiency. You'll also mentor junior engineers, helping to foster a strong culture of technical excellence and collaborative innovation.

To qualify for the Senior Engineer - Computing Architecture role at Axelera AI, candidates should hold either a Master's or PhD in Computer Engineering, Electrical Engineering, or a related field. Additionally, a minimum of 5 years of experience in computing architecture or system design is essential, ideally within AI or semiconductor domains. Strong expertise in processor design, memory hierarchies, and interconnect technologies, along with a proven track record in delivering complex computing architectures, is also required.

Yes, experience with AI workloads is crucial for the Senior Engineer - Computing Architecture position at Axelera AI. A deep understanding of AI algorithms, data flows, and performance analysis frameworks is necessary to design efficient computing architectures that can handle complex AI applications. This role involves significant collaboration with software and hardware teams, necessitating a solid foundation in AI technology.

Preferred skills for the Senior Engineer - Computing Architecture role at Axelera AI include proficiency in programming languages such as C or Python. Familiarity with high-performance computing (HPC) techniques, knowledge of hardware description languages like Verilog or VHDL, and experience designing AI accelerators will give candidates a strong edge in the application process. Additionally, expertise in power management and thermal design for embedded systems is also advantageous.

As a Senior Engineer - Computing Architecture at Axelera AI, you’ll enjoy a competitive compensation package that includes pension plans and extensive employee insurance options. The company boasts a vibrant and inclusive culture that fosters creativity and continual innovation. You will work within a supportive team that values diversity and collaboration, and you'll have the freedom to take ownership of your projects in a fast-paced international environment.

When answering this question, focus on specific projects where you've designed or developed computing architectures for AI applications. Highlight any particular technologies or frameworks you used and the challenges you overcame during implementation to demonstrate your knowledge in this area.

In your response, provide examples of optimization techniques you've applied, such as reducing power consumption or improving efficiency. Discuss specific metrics or tools you've utilized to analyze workloads and the impact of your optimizations on system performance.

Share experiences where you've successfully collaborated with different teams, emphasizing communication and teamwork. Discuss strategies you've employed to bridge gaps between hardware and software teams, and how your collaborations led to successful project outcomes.

Discuss any innovative designs or methodologies you've developed and their significance. Highlight the impact these innovations had on project success, focusing on improvements in performance or efficiency directly related to AI workloads.

Elaborate on the concept of hardware-software co-design, explaining how it contributes to the seamless integration of systems. Provide examples from your work demonstrating the advantages of co-design, particularly in enhancing performance for AI applications.

Discuss your strategies for keeping abreast of industry trends, such as reading academic papers, attending conferences, or participating in relevant online forums. Mention how you apply this knowledge in your work, particularly in evaluating new technologies for integration into your designs.

Prepare to detail a specific challenge relevant to AI computing architecture, such as overcoming power constraints or memory bottlenecks. Outline your thought process and the particular steps you took to address the issue, highlighting the successful outcome.

Explain how simulation tools contribute to validating and predicting the performance of architectural designs. Share your experience with specific modeling tools and how they have helped ensure that designs meet requirements before implementation.

Describe your approach to mentorship, focusing on hands-on guidance and support. Share examples of how you've helped junior engineers grow their skills and navigate challenges, fostering a collaborative and educational environment.

Reflect on the various factors that contribute to high performance in AI systems, such as architecture design, workload optimization, or efficient resource management. Articulate your thoughts on which factors you prioritize and why, based on your professional experience.