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- Tasks: Tackle challenging AI infrastructure problems and innovate with cutting-edge technology.
- Company: Join a forward-thinking tech company focused on AI advancements.
- Benefits: Attractive salary, flexible work options, and opportunities for skill development.
- Other info: Exciting environment with potential for rapid career advancement.
- Why this job: Be part of groundbreaking projects that shape the future of computing.
- Qualifications: Experience in high-performance systems and distributed systems is a plus.
The predicted salary is between 60000 - 80000 £ per year.
We're always looking for exceptional engineers who want to work on the hardest problems in AI infrastructure - bringing novel accelerators to life, building the systems that orchestrate them, and charting the new territories of what heterogeneous compute can do.
If you think you have unique skills to contribute, or have experience in any of the following, we'd love to hear from you:
- High-performance systems and low-level performance engineering
- Inference infrastructure, orchestration, or distributed systems
- Hardware bring-up, kernel development, or accelerator programming
- Simulation, modelling, or workload design
Share your details and we'll reach out as the right opportunities emerge.
Open Role - Systems Engineer employer: Callosum
Contact Detail:
Callosum Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Open Role - Systems Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with engineers on LinkedIn. You never know who might have the inside scoop on an open role that’s perfect for you.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to high-performance systems or distributed systems. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of inference infrastructure and kernel development. Practice coding challenges and system design questions to boost your confidence.
✨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 are proactive about their job search.
We think you need these skills to ace Open Role - Systems Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in high-performance systems and low-level performance engineering. We want to see how your unique skills align with the challenges we tackle at StudySmarter.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about AI infrastructure and how you can contribute to our mission. Be specific about your experience with inference infrastructure or distributed systems.
Showcase Relevant Projects: If you've worked on hardware bring-up, kernel development, or accelerator programming, make sure to include those projects in your application. We love seeing real-world examples of your work!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves!
How to prepare for a job interview at Callosum
✨Know Your Tech Inside Out
Make sure you’re well-versed in high-performance systems and low-level performance engineering. Brush up on your knowledge of inference infrastructure and distributed systems, as these are likely to come up during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in hardware bring-up or kernel development. Be ready to explain how you approached these problems and what solutions you implemented, as this will demonstrate your hands-on experience.
✨Familiarise Yourself with Their Projects
Research the company’s recent projects and innovations in AI infrastructure. Being able to reference their work and express how your skills can contribute to their goals will show that you’re genuinely interested and engaged.
✨Practice Simulation and Modelling Scenarios
Since workload design is a key aspect of the role, practice discussing simulation and modelling scenarios. Prepare examples of how you’ve designed workloads in the past and be ready to tackle hypothetical situations they might present.