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- Tasks: Architect AI deployment infrastructure and enhance data science platforms.
- Company: Dynamic faculty in London focused on innovative technology.
- Benefits: Hybrid working, unlimited annual leave, and competitive perks.
- Other info: Exciting opportunity for growth in a collaborative environment.
- Why this job: Join a cutting-edge team and shape the future of machine learning.
- Qualifications: Proficiency in Python, Go, Docker, Kubernetes, and MLOps tools.
The predicted salary is between 60000 - 80000 £ per year.
Faculty seeks a Software Engineer to architect infrastructure for AI deployment in London. This role involves ownership of MLOps tooling and collaboration with technologists to enhance data science platforms.
Candidates must have skills in Python, Go, Docker, and Kubernetes, with a passion for internal tools and a strong understanding of the machine learning lifecycle.
The position offers hybrid working and an unlimited annual leave policy, among other benefits.
Platform Engineer: ML Infra & MLOps Architect employer: Faculty
Contact Detail:
Faculty Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Platform Engineer: ML Infra & MLOps Architect
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working in MLOps or AI deployment. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in Python, Go, Docker, and Kubernetes. This will give potential employers a taste of what you can do and how you approach problem-solving.
✨Tip Number 3
Prepare for technical interviews by brushing up on the machine learning lifecycle. Be ready to discuss how you've used MLOps tooling in past projects. We want to see your passion for internal tools shine through!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Platform Engineer: ML Infra & MLOps Architect
Some tips for your application 🫡
Show Your Passion for MLOps: When writing your application, let us see your enthusiasm for MLOps and AI deployment. Share any personal projects or experiences that highlight your skills in Python, Go, Docker, and Kubernetes. We love seeing candidates who are genuinely excited about the tech they work with!
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter to reflect the specific requirements of the Platform Engineer role. Highlight your experience with machine learning lifecycle and internal tools, as this will show us you understand what we’re looking for. A tailored application stands out!
Be Clear and Concise: Keep your application clear and to the point. Use bullet points where possible to make it easy for us to read through your qualifications and experiences. We appreciate a well-structured application that gets straight to the good stuff!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining the StudySmarter team!
How to prepare for a job interview at Faculty
✨Know Your Tech Stack
Make sure you’re well-versed in Python, Go, Docker, and Kubernetes. Brush up on your knowledge of these technologies and be ready to discuss how you've used them in past projects. This will show that you’re not just familiar with the tools but can also apply them effectively.
✨Understand MLOps Inside Out
Since this role focuses on MLOps tooling, dive deep into the machine learning lifecycle. Be prepared to explain how you’ve implemented MLOps practices in previous roles and how they can enhance data science platforms. This will demonstrate your passion and expertise in the field.
✨Showcase Collaboration Skills
This position involves working closely with other technologists, so highlight your teamwork experiences. Think of examples where you collaborated on projects, especially those related to AI deployment or infrastructure. This will illustrate your ability to work well in a hybrid environment.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s approach to AI deployment and their internal tools. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values, especially regarding their unlimited annual leave policy.