At a Glance
- Tasks: Build and maintain AI infrastructure, empowering a team of Data Scientists and Engineers.
- Company: Join Faculty, a leader in responsible AI solutions since 2014.
- Benefits: Enjoy unlimited leave, private healthcare, and flexible working options.
- Other info: Be part of a diverse team that values innovation and collaboration.
- Why this job: Make a real impact in AI while working with cutting-edge technologies.
- 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 employer: Faculty
At Faculty, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As the Head of Banking AI Transformation, you will have the opportunity to lead transformative projects in a rapidly evolving sector while benefiting from our commitment to employee growth through continuous learning and development. Located in a vibrant area, our team enjoys a supportive environment that values diversity and encourages meaningful contributions to the financial services landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer - Platform
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or at industry events. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for those interviews! Brush up on your coding skills and be ready to discuss your past projects. We recommend practicing common technical questions and system design scenarios to show off your expertise.
✨Tip Number 3
Show your passion for AI and machine learning! During interviews, share your thoughts on recent trends or projects you've worked on. This will demonstrate your enthusiasm and fit for the role.
✨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, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Software Engineer - Platform
Some tips for your application 🫡
Show Your Passion:When writing your application, let your enthusiasm for building internal tools and AI shine through. We want to see how your passion aligns with our mission of creating responsible AI solutions.
Tailor Your Experience:Make sure to highlight your experience with Python or Go, as well as your skills in containerisation and orchestration. We’re looking for specific examples that demonstrate your ability to tackle complex infrastructure challenges.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and focus on how your skills can help us transition from exploration to production-grade ML products.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and get the ball rolling on your journey with StudySmarter.
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 show your potential employer that you can think critically and work collaboratively.
✨Understand the ML Lifecycle
Since the role involves transitioning models from exploration to production, be prepared to discuss your experience with the machine learning product lifecycle. Share specific examples of how you've contributed to this process in past roles.
✨Communicate Effectively
Remember, you’ll be working with both technical and non-technical peers. Practice explaining complex concepts in simple terms. This will not only help you during the interviews but also demonstrate your ability to collaborate within a diverse team.
