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- Tasks: Design and implement ML infrastructure to support advanced AI systems.
- Company: Cutting-edge tech firm in Greater London with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a dynamic team and shape the future of AI technology.
- Qualifications: Experience in MLOps, DevOps tooling, and cloud services like GCP or AWS.
- Other info: Exciting environment with a strong emphasis on collaboration and creativity.
The predicted salary is between 60000 - 80000 £ per year.
A cutting-edge technology firm located in Greater London is seeking a skilled MLOps Engineer with a proven track record in DevOps tooling and ML infrastructure. The ideal candidate will have experience working with platforms like ArgoCD and Jenkins, and show expertise in Infrastructure as Code using Terraform. Familiarity with cloud services such as GCP or AWS is also essential. Join a dynamic team dedicated to building advanced AI systems that enhance business outcomes.
Founding ML Infra & Platform Architect employer: Stealth
Contact Detail:
Stealth Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding ML Infra & Platform Architect
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your MLOps projects, especially those involving ArgoCD, Jenkins, and Terraform. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to ML infrastructure and be ready to discuss your experience with cloud services like GCP or AWS.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Founding ML Infra & Platform Architect
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with MLOps, DevOps tooling, and ML infrastructure. We want to see how your skills align with the job description, so don’t be shy about showcasing your expertise in platforms like ArgoCD and Jenkins!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about building advanced AI systems and how your background makes you a perfect fit for our dynamic team. Let us know what excites you about this role!
Showcase Your Projects: If you've worked on relevant projects, make sure to mention them! Whether it's using Terraform for Infrastructure as Code or deploying solutions on GCP or AWS, we love seeing real-world applications of your skills.
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 don’t miss out on any important updates. Plus, it shows us you’re keen to join our team!
How to prepare for a job interview at Stealth
✨Know Your Tech Stack
Make sure you’re well-versed in the tools mentioned in the job description, like ArgoCD, Jenkins, and Terraform. Brush up on your experience with cloud services like GCP or AWS, as you might be asked to discuss specific projects where you used these technologies.
✨Showcase Your MLOps Experience
Prepare to talk about your previous roles in MLOps and how you've contributed to building ML infrastructure. Have examples ready that demonstrate your problem-solving skills and how you’ve improved processes using DevOps tooling.
✨Understand the Company’s Vision
Research the company’s mission and recent projects. Being able to articulate how your skills align with their goals will show that you’re genuinely interested in the role and can contribute to their dynamic team.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, current challenges they face in ML infrastructure, and future projects. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.