At a Glance
- Tasks: Lead complex AI projects and architect scalable systems for impactful innovation.
- Company: Join Faculty, a leader in responsible AI with a focus on real-world impact.
- Benefits: Enjoy unlimited leave, private healthcare, and flexible working options.
- Other info: Diverse team culture that values unique perspectives and encourages growth.
- Why this job: Shape the future of AI in finance and make a meaningful difference.
- Qualifications: Expertise in machine learning and experience in financial services required.
The predicted salary is between 43200 - 72000 £ per year.
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.
In our Professional and Financial Services Business unit, we bring everything we have learned in more than a decade of Applied AI, and use it to help our clients navigate a rapidly changing landscape. We develop and embed AI solutions which help financial institutions become more efficient, enhance customer experience, and find the commercial upside in uncertain markets. Within the constraints of a highly regulated industry, we see so much opportunity for impactful innovation and are proud to set the gold‑standard for marrying technical excellence with safe deployment.
As a Principal Machine Learning Engineer, you will serve as a high‑level technical authority, steering our most complex projects and driving the next wave of AI innovation. You will architect scalable, large‑scale systems that integrate seamlessly into existing frameworks while setting the technical direction for Faculty’s flagship initiatives. By leveraging your deep expertise, you will provide authoritative advice across business units, fostering team growth and influencing company strategy to ensure our solutions remain at the cutting edge of the industry.
What you’ll be doing:
- Architecting sophisticated software and data science frameworks for large‑scale, complex systems that meet rigorous functional and non‑functional requirements.
- Designing integrated system architectures that scale effectively and align with broader organisational and technical standards.
- Solving intricate technical challenges that span multiple projects or business units, acting as a respected expert for both internal teams and external customers.
- Setting the strategic technical direction for flagship projects, providing the vision and guidance necessary to ensure successful delivery.
- Influencing company‑wide technical strategy by leveraging deep domain expertise in machine learning and advanced statistics.
- Advising major initiatives as a technical authority, ensuring that architectural choices are robust, sustainable, and innovative.
Who we’re looking for:
You are a recognised technical authority with extensive experience in machine learning, statistics, and advanced data science methodologies with a specific focus on solutions in the Financial Services space. You possess a proven track record of defining software architecture and designing complex systems that thrive within existing organisational frameworks. You’re a natural problem‑solver who can navigate challenges across diverse projects and provide authoritative guidance on major initiatives. You have the strategic mindset required to set the technical pulse for high‑impact projects and contribute meaningfully to long‑term company goals. You excel at communicating complex technical concepts to both peers and customers, earning trust through expertise and clear architectural leadership. You thrive in an entrepreneurial environment, balancing hands‑on system design with the ability to direct others toward technical excellence.
Our Interview Process:
- Talent Team Screen (30 minutes)
- Introduction to the role (45 minutes)
- Pair Programming Interview (90 minutes)
- System Design Interview (90 minutes)
- Commercial & Leadership 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.
Principal Machine Learning Engineer employer: Faculty
At Faculty, we pride ourselves on being at the forefront of AI innovation, empowering our employees to drive meaningful change in a collaborative and intellectually stimulating environment. With benefits like unlimited annual leave, private healthcare, and a strong commitment to diversity, we foster a culture that values individual contributions and encourages professional growth. Join us in London, where you can leverage your expertise as a Principal Machine Learning Engineer to shape the future of AI across various sectors while enjoying a flexible and supportive workplace.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with Faculty employees on LinkedIn. Building relationships can open doors that applications alone can't.
✨Tip Number 2
Prepare for those interviews! Brush up on your machine learning concepts and be ready to discuss your past projects. We want to see how you think and solve problems, so practice articulating your thought process.
✨Tip Number 3
Showcase your passion for AI! During interviews, share your thoughts on the future of AI and how it can impact various industries. This will demonstrate your intellectual curiosity and alignment with our mission at Faculty.
✨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 take the initiative to engage directly with us.
We think you need these skills to ace Principal Machine Learning Engineer
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience in machine learning and financial services. We want to see how your skills align with our mission of building responsible AI.
Showcase Your Expertise:Don’t hold back on sharing your technical achievements! We love seeing examples of complex systems you've designed or innovative solutions you've implemented. This is your chance to shine!
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language to explain your experience and avoid jargon unless it's necessary. We appreciate clarity as much as complexity!
Apply Through Our Website:We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Faculty
✨Know Your Stuff
As a Principal Machine Learning Engineer, you need to showcase your deep expertise in machine learning and advanced data science. Brush up on the latest trends and innovations in AI, especially those relevant to financial services. Be prepared to discuss specific projects you've worked on and the impact they had.
✨Architectural Insights
Since you'll be steering complex projects, it's crucial to articulate your approach to software architecture. Think about how you would design scalable systems that integrate seamlessly into existing frameworks. Prepare to explain your thought process and decision-making in previous roles.
✨Problem-Solving Mindset
Expect to face intricate technical challenges during the interview. Practice articulating how you've navigated similar issues in the past. Use the STAR method (Situation, Task, Action, Result) to structure your responses and demonstrate your problem-solving skills effectively.
✨Communicate Clearly
You’ll need to convey complex technical concepts to both peers and customers. Practice simplifying your explanations without losing the essence of your ideas. This will help you earn trust and show that you can lead architectural discussions with clarity and confidence.