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- Tasks: Design cutting-edge AI infrastructure for advanced workloads and enhance system performance.
- Company: Innovative tech firm based in Edinburgh, focused on AI advancements.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Join a pioneering team shaping the future of AI technology.
- Qualifications: Strong knowledge in system architecture and hands-on experience with cloud-native technologies.
- Other info: Dynamic work environment with potential for significant career advancement.
The predicted salary is between 36000 - 60000 £ per year.
Location: Edinburgh, Scotland
Type: Permanent
On-Site Working Required, No Sponsorship Provided
Responsibilities
- Design a unified AI Infra & Serving architecture platform for composite AI workloads such as LLM Training & Inference, RLHF, Agent, and Multimodal processing. This platform will integrate inference, orchestration, and state management, defining the technical evolution path for Serverless AI + Agentic Serving.
- Design a heterogeneous execution framework across CPU/GPU/NPU for agent memory, tool invocation, and long-running multi-turn conversations and tasks.
- Build an efficient memory/KV-cache/vector store/logging and state-management subsystem to support agent retrieval, planning, and persistent memory.
- Build a high-performance Runtime/Framework that defines the next-generation Serverless AI foundation through elastic scaling, cold start optimization, batch processing, function-based inference, request orchestration, dynamic decoupled deployment, and other features to support performance scenarios such as multiple models, multi-tenancy, and high concurrency.
Key Requirements
- Strong foundational knowledge in system architecture, or computer architecture, operating systems, and runtime environments.
- Hands-on experience with Serverless architectures and cloud-native optimization technologies such as containers, Kubernetes, service orchestration, and autoscaling (vLLM, SGLang, Ray Serve, etc.); understand common optimization concepts such as continuous batching, KV-Cache reuse, parallelism, and compression/quantization/distillation.
- Proficient in using Profiling/Tracing tools; experienced in analyzing and optimizing system-level bottlenecks regarding GPU utilization, memory/bandwidth, Interconnect Fabric, and network/storage paths.
- Proficient in at least one system-level language (e.g., C/C++, Go, Rust) and one scripting language (e.g., Python).
AI Infrastructure Architect in Edinburgh employer: microTECH Global Limited
Contact Detail:
microTECH Global Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Infrastructure Architect in Edinburgh
✨Tip Number 1
Network like a pro! Connect with folks in the AI and tech scene on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to AI infrastructure. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and scenarios related to AI architectures. Practice explaining your thought process clearly, as communication is key in these roles.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace AI Infrastructure Architect in Edinburgh
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Infrastructure Architect role. Highlight your experience with system architecture, cloud-native technologies, and any relevant projects that showcase your skills in serverless architectures.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI infrastructure and how your background aligns with our needs. Be specific about your hands-on experience with tools like Kubernetes and your understanding of optimization concepts.
Showcase Your Technical Skills: In your application, don’t forget to mention your proficiency in system-level languages like C/C++ or Go, as well as scripting languages like Python. We want to see how you’ve used these skills in real-world scenarios, so include examples!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at microTECH Global Limited
✨Know Your Tech Inside Out
Make sure you’re well-versed in system architecture and the specific technologies mentioned in the job description. Brush up on your knowledge of Serverless architectures, Kubernetes, and any relevant optimisation techniques. Being able to discuss these topics confidently will show that you’re the right fit for the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss past experiences where you tackled complex technical challenges. Think about how you optimised system-level bottlenecks or improved performance in previous projects. Use specific examples to illustrate your thought process and the impact of your solutions.
✨Get Familiar with Profiling Tools
Since the role requires proficiency in profiling and tracing tools, make sure you can talk about your experience with them. Be ready to explain how you’ve used these tools to analyse GPU utilisation or memory issues in the past. This will demonstrate your hands-on experience and technical depth.
✨Ask Insightful Questions
Interviews are a two-way street, so prepare some thoughtful questions about the company’s AI infrastructure and future projects. This shows your genuine interest in the role and helps you gauge if the company aligns with your career goals. Plus, it gives you a chance to engage with your interviewers on a deeper level.
