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- Tasks: Design cutting-edge AI infrastructure for advanced workloads and optimise performance across various platforms.
- Company: Join a forward-thinking tech company focused on innovation and collaboration.
- Benefits: Enjoy a fully remote role with competitive pay and opportunities for professional growth.
- Why this job: Be at the forefront of AI technology and shape the future of serverless architecture.
- Qualifications: Strong knowledge in system architecture and hands-on experience with cloud-native technologies required.
- Other info: Ideal for tech enthusiasts eager to tackle complex challenges in a dynamic 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.
Network Infrastructure Architect - Fully Remote in Edinburgh employer: Microtech Global Ltd
Contact Detail:
Microtech Global Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Network Infrastructure Architect - Fully Remote in Edinburgh
✨Tip Number 1
Network with industry professionals! Join online forums or LinkedIn groups related to AI infrastructure. Engaging in conversations can lead to valuable connections and even job leads.
✨Tip Number 2
Showcase your skills through projects! Create a portfolio that highlights your experience with Serverless architectures and cloud-native technologies. This will give potential employers a clear view of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by practising common system architecture questions. We recommend using mock interviews to get comfortable with articulating your thought process and problem-solving skills.
✨Tip Number 4
Apply directly 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 with us directly.
We think you need these skills to ace Network Infrastructure Architect - Fully Remote in Edinburgh
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Network Infrastructure Architect. 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 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 profiling tools.
Showcase Relevant Projects: If you've worked on projects that relate to the responsibilities listed in the job description, make sure to include them. We love seeing real-world applications of your skills, especially in areas like multi-tenancy and high concurrency.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Don’t forget to double-check your details before hitting send!
How to prepare for a job interview at Microtech Global Ltd
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of system architecture and cloud-native technologies. Be ready to discuss your hands-on experience with Serverless architectures, Kubernetes, and any optimisation techniques you've used. This will show that you’re not just familiar with the concepts but can apply them in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in previous roles, especially related to GPU utilisation or memory management. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easier for the interviewer to see how you approach complex problems.
✨Demonstrate Your Passion for AI
Since the role involves designing AI infrastructure, express your enthusiasm for AI technologies. Share any personal projects or research you've done in this area. This not only highlights your interest but also shows that you stay updated with industry trends.
✨Ask Insightful Questions
Prepare a few thoughtful questions about the company's AI initiatives or their approach to serverless architectures. This demonstrates your genuine interest in the role and helps you gauge if the company aligns with your career goals.
