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- Tasks: Design cutting-edge AI infrastructure for advanced workloads and enhance performance across various platforms.
- Company: Join a forward-thinking tech company at the forefront of AI innovation.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Why this job: Be part of a revolutionary 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 endless possibilities for career advancement.
The predicted salary is between 72000 - 108000 £ per year.
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.
- Understanding of 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 Dunfermline employer: Microtech Global Ltd
Contact Detail:
Microtech Global Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Infrastructure Architect in Dunfermline
✨Tip Number 1
Network like a pro! Attend industry meetups, webinars, and conferences related to AI and infrastructure. It's a great way to connect with potential employers and learn about job openings that might not be advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving serverless architectures or cloud-native technologies. This gives you a chance to demonstrate your expertise beyond just your CV.
✨Tip Number 3
Prepare for interviews by brushing up on system architecture concepts and hands-on experience with tools like Kubernetes and profiling tools. We recommend doing mock interviews to get comfortable with technical questions.
✨Tip Number 4
Don't forget to apply through our website! We often have exclusive job listings that you won't find elsewhere. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace AI Infrastructure Architect in Dunfermline
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the AI Infrastructure Architect role. Highlight your experience with serverless architectures and cloud-native technologies, as these are key for us.
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 makes you a perfect fit for our team at StudySmarter.
Showcase Your Projects: If you've worked on relevant projects, don’t hold back! Include links or descriptions of your work that demonstrate your hands-on experience with system architecture and optimization techniques.
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 without any hiccups!
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 come up in the interview. Think about examples from your past experience that showcase your understanding of these concepts.
✨Hands-On Experience Matters
Prepare to talk about your hands-on experience with Serverless architectures and cloud-native technologies. Have specific examples ready where you've implemented solutions using containers, Kubernetes, or service orchestration. This will show that you can apply your theoretical knowledge in practical scenarios.
✨Optimisation is Key
Familiarise yourself with common optimisation concepts like continuous batching and KV-Cache reuse. Be prepared to discuss how you've tackled system-level bottlenecks in previous roles, especially regarding GPU utilisation and memory management. This will demonstrate your problem-solving skills and technical depth.
✨Show Off Your Coding Skills
Since proficiency in system-level languages like C/C++, Go, or Rust is crucial, be ready to discuss your coding experience. You might even be asked to solve a coding problem during the interview, so practice some relevant coding challenges beforehand to boost your confidence.
