At a Glance
- Tasks: Build and maintain AI infrastructure, empowering data scientists and engineers.
- Company: Innovative AI solutions provider with a focus on responsible technology.
- Benefits: Unlimited annual leave, private healthcare, flexible working, and enhanced parental leave.
- Other info: Diverse and inclusive workplace with excellent career growth opportunities.
- Why this job: Join a passionate team and shape the future of AI technology.
- Qualifications: Experience in Python or Go, containerisation, and Infrastructure-as-Code.
The predicted salary is between 60000 - 80000 € per year.
Faculty was founded in 2014 to build responsible AI solutions for diverse industries. We serve over 350 customers and value intellectual curiosity.
As a Software Engineer in the AI Platform team, you will be the architect of the infrastructure that makes world‑class AI possible. Working closely with the Applied AI team, you’ll build and maintain data‑science, MLOps, and deployment tooling that empowers our team of over 100 Data Scientists and Engineers. You will own the platform that enables us to transition from exploration to production‑grade ML products, ensuring high‑performance, scalability, and seamless integration into diverse client environments.
What You’ll Be Doing
- Taking ownership of our existing deployment and MLOps tooling to ensure our software delivery remains a significant lever for quality and reliability.
- Contributing to the continuous evolution of our technology stack, from building new features in our notebook development environments to refining model monitoring systems.
- Collaborating with a small, fast‑moving team of customer‑facing technologists to design and build the infrastructure our delivery teams need to succeed.
- Designing and implementing infrastructure‑as‑code and DevSecOps processes to support distributed, containerised microservices architectures.
- Integrating our core platform services across multiple cloud environments, including AWS, Azure, and GCP, to provide flexible solutions for our global clients.
- Scaling our internal enablement capabilities, acting as an entrepreneurial force that removes technical friction and accelerates the deployment of machine learning.
Who We’re Looking For
- You are a Software Engineer who is passionate about building internal tools and takes pride in creating the foundational systems that enable others to excel.
- You understand the nuances of the machine learning product lifecycle and have a clear vision for how to move models efficiently from exploration to production.
- You possess modern systems programming skills in Python or Go and are comfortable selecting the best‑fit technology for complex infrastructure challenges.
- You bring practical experience with containerisation and orchestration, specifically using Docker and Kubernetes to manage distributed systems at scale.
- You have a strong background in Infrastructure‑as‑Code (IaaC) using tools like Terraform or CloudFormation, combined with a deep interest in DevSecOps practices.
- You thrive in small, ambitious teams where you can take high levels of ownership and communicate effectively with both technical and non‑technical peers.
Our Interview Process
- Talent Team Screen (30 minutes)
- Pair Programming Interview (90 minutes)
- System Design Interview (90 minutes)
- Commercial Interview (60 minutes)
Our Recruitment Ethos
We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions, and sexual orientations. Diversity of individuals fosters diversity of thought, strengthening our ability to deliver measurable positive impact.
Some Of Our Standout Benefits
- Unlimited Annual Leave Policy
- Private healthcare and dental
- Enhanced parental leave
- Family‑Friendly Flexibility & Flexible working
- Sanctus Coaching
- Hybrid Working
Software Engineer - Platform in London employer: Faculty
At Faculty, we pride ourselves on being an exceptional employer that champions innovation and collaboration in the AI space. Our commitment to employee growth is reflected in our unlimited annual leave policy, private healthcare, and a family-friendly work culture that embraces flexibility and hybrid working. Join us in a dynamic environment where your contributions directly impact the development of cutting-edge AI solutions for a diverse range of clients.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer - Platform in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and MLOps. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common technical questions and coding challenges. Use platforms like LeetCode or HackerRank to sharpen your skills. Remember, confidence is key!
✨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 genuinely interested in joining our team.
We think you need these skills to ace Software Engineer - Platform in London
Some tips for your application 🫡
Show Your Passion:When you're writing your application, let your enthusiasm for building internal tools and AI solutions shine through. We love seeing candidates who are genuinely excited about the role and the impact they can make!
Tailor Your Experience:Make sure to highlight your experience with Python or Go, as well as any work you've done with containerisation and orchestration. We want to see how your skills align with what we’re looking for, so don’t hold back!
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and focus on what makes you a great fit for our team. Remember, less is often more!
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’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Faculty
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, Go, Docker, and Kubernetes. Brush up on your Infrastructure-as-Code skills with Terraform or CloudFormation, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
During the pair programming interview, focus on demonstrating your thought process. Don’t just code; explain your reasoning and how you approach challenges. This will help the interviewers see your problem-solving abilities in action.
✨Understand the ML Lifecycle
Since the role involves transitioning models from exploration to production, be prepared to discuss the machine learning product lifecycle. Share examples of how you've contributed to this process in past projects, highlighting your understanding of MLOps.
✨Communicate Effectively
In a small team environment, communication is key. Practice explaining complex technical concepts in simple terms, as you’ll need to collaborate with both technical and non-technical peers. This will show that you can bridge the gap between different team members.
