Distinguished Engineer - Machine Learning

As a Distinguished Engineer in Machine Learning at Axelera AI, you will own and lead company-wide AI initiatives, providing strategic direction and influencing multi-team projects. Your role includes driving R&D for innovative AI and ML models while ensuring best engineering practices are followed. You will mentor senior engineers, bridge the gap between technical capabilities and business needs, and represent Axelera AI at conferences, making your contributions vital to the company's success.

To qualify as a Distinguished Engineer in Machine Learning at Axelera AI, candidates should possess a PhD in Computer Science, Machine Learning, or related fields, along with 10+ years of post-doctoral experience in AI/ML research and development. A strong background in relevant AI frameworks, deep learning algorithms, and experience in managing and mentoring engineers is essential to excel in this role.

Axelera AI offers a flexible working arrangement for the Distinguished Engineer position, allowing you to either work from one of our offices located in various European cities or fully remotely from your current location within Europe or the UK. This flexibility is key to fostering innovation and work-life balance, making it easier to achieve your professional goals.

The Distinguished Engineer position at Axelera AI is designed for significant career growth, offering opportunities to influence technical directions and drive large-scale impactful projects. You will have a platform to publish research, present at conferences, and lead initiatives that shape the future of AI technology, which not only enhances your experience but positions you as a leader in the AI community.

Axelera AI offers an attractive compensation package for its Distinguished Engineers, which includes a pension plan, extensive employee insurances, and options for company shares. Additionally, the company fosters a culture of creativity, collaboration, and individual responsibility, ensuring that team members have the necessary support to thrive personally and professionally.

As a Distinguished Engineer, leading a large-scale AI project begins with setting clear objectives and engaging with cross-functional teams to align on the vision. I would utilize Agile methodologies to manage project phases while ensuring transparency and adaptability, facilitating communication across departments to address challenges promptly.

Certainly! I have extensive experience with various AI frameworks such as TensorFlow and PyTorch, utilizing deep learning algorithms to enhance model performance. My focus has been on developing adaptive models that can be deployed efficiently in different environments, ensuring optimal use of resources and maintaining high predictive accuracy.

Fostering innovation starts with creating an open environment where team members feel safe to share ideas. I encourage brainstorming sessions, provide resources for exploration, and promote an iterative process where feedback is valued. Recognizing contributions and celebrating successes also helps to motivate and inspire the team.

When mentoring junior engineers, I prioritize establishing a supportive relationship and tailoring learning opportunities to their individual needs. I provide hands-on guidance, share real-world examples, and encourage independent problem-solving. Regular check-ins and constructive feedback are crucial for their growth and confidence in their skills.

Addressing ambiguity involves thorough communication with stakeholders to gather as much clarity as possible. I encourage iterative discussions to identify key objectives and iterate on requirements as the project unfolds. Prototyping can also help clarify needs and expectations, allowing the team to remain agile.

In my previous role, I led a research initiative that resulted in a revolutionary AI model, improving processing efficiency by 40%. This involved cross-disciplinary collaboration, and we integrated neuromorphic computing techniques, which set a new benchmark in the industry. The success was a combination of innovative thinking and rigorous testing.

Collaboration is at the heart of my engineering philosophy. I believe that diverse perspectives lead to superior solutions. Encouraging team synergy and involving stakeholders in the decision-making process not only enhances project outcomes but also fosters a culture of shared ownership and responsibility.

I proactively engage with the AI community by attending conferences, participating in workshops, and reading recent publications. I also contribute to open-source projects and collaborate with thought leaders, which keeps my skill set sharp and ensures I’m abreast of emerging trends that could influence our strategic direction.

I have worked on projects that focused on optimizing machine learning algorithms for specific hardware architectures, such as GPUs and TPUs. This experience has allowed me to enhance model performance and efficiency by implementing hardware-aware training techniques that make the most out of the underlying compute resources.

Success as a Distinguished Engineer is defined by the tangible impact I can make on the organization and the community. This includes driving innovations that lead to substantial business outcomes, mentoring engineers to excel in their careers, and contributing to the broader AI landscape through research and engagement.