At a Glance
- Tasks: Build and deploy impactful machine learning solutions for diverse clients.
- Company: Join Faculty, a leader in human-centric AI transformation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic team environment with excellent career advancement opportunities.
- Why this job: Work with brilliant minds and make a real-world impact with AI.
- Qualifications: Experience in machine learning frameworks and strong Python skills required.
The predicted salary is between 36000 - 60000 £ 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 as Docker.
Machine Learning Engineer 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 Machine Learning Engineer
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Faculty or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Faculty.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Faculty.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Faculty that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Faculty.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Faculty and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Faculty
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Faculty uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
