At a Glance
- Tasks: Develop and optimise high-performance kernels for ML operators on NPU architectures.
- Company: Join a dynamic team at the forefront of AI technology.
- Benefits: Collaborative environment, competitive salary, and opportunities for professional growth.
- Other info: Ideal for those looking to lead and mentor in a cutting-edge tech space.
- Why this job: Make a real impact in AI by creating innovative products and services.
- Qualifications: Experience in kernel development, proficiency in OpenCL or CUDA, and strong C++ skills.
The predicted salary is between 43200 - 72000 £ per year.
We are seeking a skilled Senior Compute Library Engineer to join our team in developing and optimising high-performance kernels for ML operators on NPU architectures. As part of this role, you will work with talented engineers to create innovative products, services, and customer experiences.
Requirements:
- Extensive experience in kernel development projects for GPUs
- Proficiency in OpenCL, CUDA or similar parallel programming languages
- A strong understanding of ML frameworks - TensorFlow, PyTorch etc.
- Mastery of C++ development skills
- Experience leading teams or mentoring junior engineers is desirable but not essential
We offer a collaborative working environment where your ideas can flourish into impactful solutions.
AI Architectural Expert in Cambridge employer: beBeeArtificial
Join a forward-thinking company that values innovation and collaboration, where as an AI Architectural Expert, you will have the opportunity to work alongside talented engineers in a dynamic environment. We prioritise employee growth through mentorship and continuous learning, ensuring that your contributions lead to meaningful advancements in technology. Located in a vibrant area, our workplace fosters creativity and offers unique benefits that enhance both professional and personal development.
StudySmarter Expert Advice🤫
We think this is how you could land AI Architectural Expert in Cambridge
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work with NPU architectures or ML frameworks. A friendly chat can lead to insider info about job openings that might not even be advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to kernel development and parallel programming. This is your chance to demonstrate your expertise in OpenCL, CUDA, and C++ – make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of ML frameworks like TensorFlow and PyTorch. Be ready to discuss how you've used these tools in past projects, as this will show you're the perfect fit for our team.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace AI Architectural Expert in Cambridge
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with kernel development and parallel programming languages like OpenCL or CUDA. We want to see how your skills align with the role, so don’t be shy about showcasing your expertise!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for ML frameworks and how you've contributed to similar projects in the past. We love hearing about your journey and what drives you to apply for this role.
Showcase Teamwork and Leadership:Even if you haven’t led a team before, highlight any mentoring experiences or collaborative projects. We value a team player who can contribute to our innovative environment, so let us know how you work well with others!
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at beBeeArtificial
✨Know Your Kernels
Make sure you brush up on your kernel development knowledge, especially for GPUs. Be ready to discuss specific projects you've worked on and the challenges you faced. This will show your depth of experience and problem-solving skills.
✨Show Off Your Programming Skills
Since proficiency in OpenCL, CUDA, or similar languages is key, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice coding challenges related to parallel programming before the interview.
✨Familiarise Yourself with ML Frameworks
Get comfortable discussing TensorFlow and PyTorch. Be prepared to explain how you've used these frameworks in past projects, and think about how they relate to the role you're applying for. This will highlight your relevant experience.
✨Emphasise Collaboration
Since the role involves working with talented engineers, be ready to talk about your teamwork experiences. Share examples of how you've collaborated on projects or mentored junior engineers, even if it's not a requirement. It shows you're a team player!
