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- Tasks: Design cutting-edge AI infrastructure for advanced workloads and enhance system performance.
- Company: Join a forward-thinking tech company in Edinburgh, shaping the future of AI.
- Benefits: Competitive salary, professional growth, and a chance to work with innovative technologies.
- Why this job: Be at the forefront of AI technology and make a significant impact on the industry.
- Qualifications: Strong knowledge in system architecture and hands-on experience with cloud-native technologies.
- Other info: Exciting opportunity for career advancement in a dynamic, collaborative environment.
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).
If you're interested in applying, please reach out to daniel@microtech-global.com.
Infrastructure Architect in Edinburgh employer: Microtech Global Ltd
Contact Detail:
Microtech Global Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Infrastructure Architect in Edinburgh
✨Tip Number 1
Network like a pro! Connect with folks in the industry on LinkedIn or at local meetups. We can’t stress enough how important it is to build relationships; you never know who might have the inside scoop on job openings.
✨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 system architecture and cloud-native technologies. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Infrastructure Architect in Edinburgh
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Infrastructure Architect role. Highlight your experience with system architecture and cloud-native technologies, as these are key for us. Use specific examples that showcase your skills in designing and optimising AI infrastructures.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're passionate about AI infrastructure and how your background aligns with our needs. Be sure to mention any hands-on experience you have with Serverless architectures and optimisation technologies.
Showcase Relevant Projects: If you've worked on projects related to AI workloads or system-level optimisations, make sure to include them. We love seeing real-world applications of your skills, so don’t hold back on the details!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Microtech Global Ltd
✨Know Your Architecture
Make sure you brush up on your knowledge of system and computer architecture. Be ready to discuss how you would design a unified AI infrastructure platform, as this will likely be a key focus during the interview.
✨Hands-On Experience Matters
Prepare to share specific examples of your hands-on experience with Serverless architectures and cloud-native technologies. Highlight any projects where you've used containers, Kubernetes, or service orchestration to optimise performance.
✨Optimisation Concepts Are Key
Familiarise yourself with optimisation concepts like continuous batching and KV-Cache reuse. Be prepared to explain how you've applied these concepts in past roles to tackle system-level bottlenecks.
✨Showcase Your Coding Skills
Since proficiency in system-level languages is crucial, be ready to discuss your experience with languages like C/C++, Go, or Rust. You might even want to prepare for a coding challenge or technical questions related to these languages.
