At a Glance
- Tasks: Build and maintain AI infrastructure, empowering data scientists and engineers.
- Company: Join Faculty, a leader in responsible AI innovation since 2014.
- Benefits: Enjoy unlimited leave, private healthcare, and flexible working options.
- Other info: Diverse team culture with excellent growth opportunities.
- Why this job: Make a real impact in AI while working with cutting-edge technology.
- Qualifications: Experience in Python or Go, containerisation, and Infrastructure-as-Code.
The predicted salary is between 60000 - 80000 € per year.
Why Faculty? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.
Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen.
About the role: 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 be building and maintaining the data science, MLOps, and deployment tooling that empowers our team of over 100 Data Scientists and Engineers. You will take ownership of the platform that enables us to transition from complex exploration to full-stack, production-grade machine learning products, ensuring our solutions are high-performing, scalable, and seamlessly integrated 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 you 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 aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
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
If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.
Software Engineer - Platform in London employer: Faculty AI
At Faculty, we pride ourselves on being at the forefront of AI innovation, empowering our employees to shape the future of technology in a collaborative and intellectually stimulating environment. With a strong commitment to employee well-being, we offer exceptional benefits such as unlimited annual leave, private healthcare, and family-friendly flexibility, ensuring that our team can thrive both personally and professionally. Join us in a culture that values diversity, encourages growth, and fosters a sense of ownership, making it an ideal place for passionate Software Engineers to make a meaningful impact.
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 current employees at Faculty on LinkedIn or other platforms. Ask them about their experiences and the company culture. This not only shows your interest but can also give you insider tips that might help you stand out during the interview.
✨Tip Number 2
Prepare for those technical interviews! Brush up on your Python or Go skills, and get comfortable with containerisation tools like Docker and Kubernetes. Practising pair programming can also be a game-changer, so find a buddy and tackle some coding challenges together.
✨Tip Number 3
Show off your passion for AI! During interviews, share your thoughts on the latest trends in AI and how you envision its applications. This will demonstrate your intellectual curiosity and align with Faculty's mission of building responsible AI solutions.
✨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 Faculty and being part of our exciting journey in AI.
We think you need these skills to ace Software Engineer - Platform in London
Some tips for your application 🫡
Show Your Passion for AI:When writing your application, let us see your enthusiasm for AI and how it can transform industries. Share any relevant projects or experiences that highlight your interest in building impactful technology.
Tailor Your CV and Cover Letter:Make sure to customise your CV and cover letter to reflect the specific skills and experiences mentioned in the job description. We want to see how your background aligns with our needs, so don’t hold back on showcasing your relevant expertise!
Be Clear and Concise:Keep your application straightforward and to the point. Use clear language to describe your experiences and achievements, making it easy for us to understand your qualifications and how you can contribute to our team.
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 shows us you’re keen to join our team!
How to prepare for a job interview at Faculty AI
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, especially Python, Go, Docker, Kubernetes, and Infrastructure-as-Code tools like Terraform. Be ready to discuss your experience with these technologies and how you've used them in past projects.
✨Showcase Your Problem-Solving Skills
During the pair programming interview, focus on demonstrating your thought process. Explain your reasoning as you tackle problems, and don't hesitate to ask clarifying questions. This shows your collaborative spirit and ability to communicate effectively with both technical and non-technical peers.
✨Understand the AI Landscape
Since Faculty is all about human-centric AI, brush up on current trends and challenges in AI and machine learning. Be prepared to discuss how you envision applying AI in real-world scenarios and how your role as a Software Engineer can contribute to that vision.
✨Emphasise Team Collaboration
Highlight your experience working in small, agile teams. Share examples of how you've taken ownership of projects and collaborated with others to achieve common goals. This aligns with Faculty's ethos of fostering diverse teams and encourages a positive legacy through technology.
