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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 (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 Broughton 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 Broughton
✨Tip Number 1
Network like a pro! Attend industry meetups, webinars, or 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! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI Infrastructure Architect in Broughton
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 building efficient AI platforms.
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 serverless architectures and optimization techniques.
Showcase Your Technical Skills: Don’t forget to highlight your proficiency in system-level languages like C/C++ or Go, as well as scripting languages like Python. Mention any tools you’ve used for profiling and tracing, as these are key to the role.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Microtech Global Ltd
✨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 not just familiar with them, but that you can apply them effectively.
✨Showcase Your Problem-Solving Skills
Prepare to discuss past experiences where you’ve tackled system-level bottlenecks or optimised performance. Use specific examples to illustrate your thought process and the impact of your solutions. This will demonstrate your hands-on experience and ability to think critically under pressure.
✨Practice Coding and Scripting
Since proficiency in system-level languages like C/C++, Go, or Rust is crucial, make sure to brush up on your coding skills. You might be asked to solve a problem on the spot, so practice common algorithms and data structures. Also, don’t forget to review Python scripting as it’s equally important for this role.
✨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.
