At a Glance
- Tasks: Develop and maintain tools for AI research, deploying services with Kubernetes and Docker.
- Company: Join Graphcore, a leader in AI compute backed by SoftBank Group.
- Benefits: Competitive salary, growth opportunities, and a chance to work on cutting-edge technology.
- Other info: Dynamic team culture focused on innovation and long-term solutions.
- Why this job: Make a real impact in the future of AI while working with top experts.
- Qualifications: Experience with software development, Kubernetes, and Docker is a plus.
The predicted salary is between 60000 - 80000 £ per year.
About Graphcore
At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacentre scale. As part of the SoftBank Group, backed by significant long‑term investment, we are delivering key technology into the fast‑growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world. We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.
Job Summary
Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High‑Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems.
The Team
The Software Infrastructure team provides critical platforms and services for software development teams across the business. Our responsibilities include managing the CI platform and services, build engineering, component integration, and packaging and release systems. We operate in squads, fostering a culture of service ownership and empowerment for our engineers. We focus on long‑term engineering solutions and strive to eliminate toil wherever possible.
Responsibilities and Duties
- Develop, own, and maintain tools and services to support AI research and engineering teams
- Deploy and maintain services with Kubernetes and Docker
Infrastructure and MLOps Engineer employer: EngineersOfAI
Graphcore is an exceptional employer, offering a vibrant work culture where innovation thrives and every team member has the chance to make a significant impact on the future of AI technology. With a strong focus on employee growth, we provide opportunities for professional development within a supportive environment backed by the resources of the SoftBank Group. Located in a dynamic tech hub, our team enjoys access to cutting-edge projects and collaboration with some of the brightest minds in the industry.
StudySmarter Expert Advice🤫
We think this is how you could land Infrastructure and MLOps Engineer
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at EngineersOfAI or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to EngineersOfAI.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like EngineersOfAI.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like EngineersOfAI that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Infrastructure and MLOps Engineer
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at EngineersOfAI.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at EngineersOfAI and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at EngineersOfAI
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If EngineersOfAI uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
