Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join our team to build and support cutting-edge AI/ML infrastructure solutions.
- Company: Be part of a dynamic company at the forefront of AI technology.
- Benefits: Enjoy flexible work options, competitive pay, and exciting corporate perks.
- Why this job: Work hands-on with innovative technologies and collaborate with top talent in the field.
- Qualifications: 6+ years in cloud environments; expertise in AI/ML frameworks and infrastructure as code.
- Other info: Ideal for self-starters who thrive under pressure and love problem-solving.
The predicted salary is between 43200 - 72000 £ per year.
This role is a member of the AI/ML Infrastructure Engineering team and will be dedicated to implementing and supporting AI/ML infrastructure solutions in cloud and on-premise environments. The role will work directly with infrastructure teams and potentially face off with data scientists, machine learning engineers, application developers, and quantitative analysts by functioning as both a solutions architect and a professional services engineer. This is a hands-on developer role, and candidates ideally have had experience deploying and supporting their own production-ready AI/ML models in cloud environments as well as automating the build and management of a broad range of cloud infrastructure using tools like Terraform.
Candidates should be familiar with developing unit and functional tests, have experience designing and implementing CI/CD tools with infrastructure as code pipelines, and have knowledge of Linux systems administration, containerization, networking, security, automated configuration and state management, cross-system orchestration, configuration management, logging, metrics, monitoring, and alerting.
Principal Responsibilities:- Architect, develop and maintain internal AI/ML infrastructure components, frameworks, and offerings
- Architect, develop and maintain AI/ML solutions for customers in cloud environments
- Help customers architect, develop and maintain their own AI/ML solutions in cloud environments
- Implement CI/CD pipelines which include application tests, security tests, and gates
- Implement availability, security, performance monitoring, and alerting of AI/ML solutions
- Automate data resiliency and replication for AI/ML models
- Manage multiple environments and promote code between them
- Automate systems configuration and orchestration using tools such as Terraform, Chef, Ansible, or Salt
- Automate creation of machine images and containers
- 6+ years of experience designing and supporting production cloud environments
- Experience consulting with customers to develop AI/ML solutions
- Experience developing collaboratively, including infrastructure as code, preferably in Python
- Systems engineering knowledge, including understanding of Linux, security, and networking
- Cloud templating tools such as Terraform
- Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch)
- Experience with distributed computing tools (e.g., Ray, Dask)
- Experience with model serving tools (e.g., vLLM, KFServing)
- Experience with building, monitoring, and alerting on logs and metrics
- Cloud Networking including connectivity, routing, DNS, VPCs, proxies, and load balancers
- Cloud Security including IAM, Certificate Management, and Key Management
- Excellent written and verbal communication skills
- Excellent troubleshooting and analytical skills
- Self-starter able to execute independently, on a deadline, and under pressure
ML Infrastructure Engineer employer: Millennium
Contact Detail:
Millennium Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Infrastructure Engineer
✨Tip Number 1
Familiarise yourself with the specific AI/ML frameworks mentioned in the job description, such as TensorFlow and PyTorch. Having hands-on experience with these tools will not only boost your confidence but also demonstrate your capability to potential employers.
✨Tip Number 2
Showcase your experience with cloud infrastructure automation tools like Terraform, Chef, or Ansible. Be prepared to discuss specific projects where you implemented these tools, as this will highlight your practical skills and problem-solving abilities.
✨Tip Number 3
Brush up on your knowledge of CI/CD pipelines and how they relate to AI/ML solutions. Understanding how to implement application tests and security gates will be crucial, so consider preparing examples of how you've successfully integrated these practices in past roles.
✨Tip Number 4
Network with professionals in the AI/ML field, especially those who work with infrastructure. Engaging in discussions about current trends and challenges can provide valuable insights and may even lead to referrals for positions like the one we have at StudySmarter.
We think you need these skills to ace ML Infrastructure Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI/ML infrastructure, cloud environments, and tools like Terraform. Use specific examples of projects where you've deployed production-ready models or automated infrastructure.
Craft a Strong Cover Letter: In your cover letter, express your passion for AI/ML and how your skills align with the role. Mention your experience with CI/CD pipelines, systems administration, and any direct interactions with data scientists or engineers.
Showcase Technical Skills: Clearly list your technical skills related to the job description, such as experience with Linux, cloud security, and AI/ML frameworks. Provide context on how you've applied these skills in previous roles.
Prepare for Technical Questions: Anticipate technical questions related to your experience with cloud infrastructure, automation tools, and AI/ML solutions. Be ready to discuss specific challenges you've faced and how you overcame them.
How to prepare for a job interview at Millennium
✨Showcase Your Hands-On Experience
Be prepared to discuss specific projects where you've deployed and supported AI/ML models in cloud environments. Highlight your hands-on experience with tools like Terraform, as this will demonstrate your practical skills and understanding of the role.
✨Understand the Infrastructure Landscape
Familiarise yourself with the various components of AI/ML infrastructure, including CI/CD pipelines, containerisation, and cloud security. Being able to articulate how these elements work together will show that you have a comprehensive understanding of the infrastructure you'll be working with.
✨Prepare for Technical Questions
Expect technical questions related to Linux systems administration, networking, and security. Brush up on your knowledge of these areas, as well as your experience with AI/ML frameworks like TensorFlow or PyTorch, to confidently answer any queries that come your way.
✨Demonstrate Strong Communication Skills
Since this role involves collaboration with various teams, it's crucial to showcase your communication skills. Be ready to explain complex technical concepts in simple terms, and provide examples of how you've successfully worked with cross-functional teams in the past.
