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For Companies At a Glance
- Tasks: Build and deploy impactful machine learning solutions for diverse clients.
- Company: Join Faculty, a leader in human-centric AI with a collaborative culture.
- Benefits: Competitive salary, diverse team, and opportunities for professional growth.
- Why this job: Work with brilliant minds and transform industries through cutting-edge AI technology.
- Qualifications: Experience in machine learning frameworks and strong Python skills required.
- Other info: Fast-paced environment with excellent career development opportunities.
The predicted salary is between 28800 - 48000 ÂŁ per year.
About Faculty
At Faculty, we transform organisational performance through safe, impactful and human‑centric AI. With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us, you’ll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world.
About the team
Our Retail and Consumer experts are dedicated to helping clients in an industry which is being transformed by new technologies and evolving consumer expectations. Leveraging over a decade of experience in Applied AI, we combine exceptional technical and delivery expertise to empower businesses to adapt and thrive.
About the role
Join us as a Machine Learning Engineer to deliver bespoke, impactful AI solutions for our diverse clients. You will be instrumental in bringing machine learning out of the lab and into the real world, contributing to scalable software architecture and defining best practices. Working with clients, and cross‑functional teams, you'll ensure technical feasibility and timely delivery of high‑quality, production‑grade ML systems.
What you’ll be doing:
- Building and deploying production‑grade ML software, tools, and infrastructure.
- Creating reusable, scalable solutions that accelerate the delivery of ML systems.
- Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges.
- Leading technical scoping and architectural decisions to ensure project feasibility and impact.
- Defining and implementing Faculty’s standards for deploying machine learning at scale.
- Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders.
Who we’re looking for:
- You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit‑learn, TensorFlow, or PyTorch.
- You possess strong Python skills and solid experience in software engineering best practices.
- You bring hands‑on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security.
- You’ve worked with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale.
- You are comfortable with core ML concepts, including probability, statistics, and common learning techniques.
- You’re an excellent communicator, able to guide technical teams and confidently advise non‑technical stakeholders.
- You thrive in a fast‑paced environment, and enjoy the autonomy to own scope, solve and deliver solutions.
The Interview Process
- Talent Team Screen (30 minutes)
- Pair Programming Interview (90 minutes)
- System Design Interview (90 minutes)
- Commercial Interview (60 minutes)
What we can offer you:
The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.
Machine Learning Engineer in City of London employer: Faculty
Contact Detail:
Faculty Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in City of London
✨Tip Number 1
Network like a pro! Reach out to current or former Faculty employees on LinkedIn. Ask them about their experiences and any tips they might have for the interview process. Personal connections can give you insights that you won't find anywhere else.
✨Tip Number 2
Prepare for those technical interviews! Brush up on your machine learning concepts and be ready to discuss your past projects. Practising coding challenges on platforms like LeetCode can help you feel more confident when it comes to the pair programming interview.
✨Tip Number 3
Showcase your communication skills! During the interviews, make sure to explain your thought process clearly. Remember, you’ll be working with non-technical stakeholders, so demonstrating your ability to translate complex ideas into simple terms 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, it shows you’re genuinely interested in joining the Faculty team and contributing to impactful AI solutions.
We think you need these skills to ace Machine Learning Engineer in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with frameworks like Scikit-learn, TensorFlow, or PyTorch, and don’t forget to showcase your Python skills and cloud platform experience!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and how your skills align with our mission at Faculty. Be genuine and let your personality come through.
Showcase Your Projects: If you've worked on any relevant projects, make sure to include them in your application. Whether it's a personal project or something from your previous job, demonstrating your hands-on experience can really set you apart.
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 you’re keen on joining our team!
How to prepare for a job interview at Faculty
✨Know Your ML Frameworks
Make sure you’re well-versed in the machine learning frameworks mentioned in the job description, like Scikit-learn, TensorFlow, and PyTorch. Brush up on your experience with these tools and be ready to discuss specific projects where you've operationalised models.
✨Showcase Your Python Skills
Since strong Python skills are a must, prepare to demonstrate your coding abilities during the pair programming interview. Practice common algorithms and data structures in Python, and be ready to explain your thought process as you code.
✨Understand Cloud Platforms
Familiarise yourself with cloud platforms like AWS, Azure, or GCP. Be prepared to discuss how you've used these platforms in past projects, especially regarding architecture and security. This will show that you can handle the infrastructure side of machine learning.
✨Communicate Clearly
As an excellent communicator, you’ll need to translate complex ML concepts for non-technical stakeholders. Practice explaining your past projects in simple terms, focusing on the impact and outcomes rather than just the technical details.
