At a Glance
- Tasks: Lead innovative AI projects and set technical direction for machine learning solutions.
- Company: Join Faculty, a pioneering AI company transforming industries with human-centric technology.
- Benefits: Enjoy unlimited leave, private healthcare, flexible working, and coaching support.
- Other info: Diverse and inclusive environment with opportunities for personal and professional growth.
- Why this job: Shape the future of AI in retail and make a real impact on businesses.
- Qualifications: Expertise in Python, cloud solutions, and experience leading engineering teams.
The predicted salary is between 80000 - 100000 £ 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 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 Lead Machine Learning Engineer to spearhead the technical direction and delivery of complex, innovative AI projects. You will act as a technical expert, applying your skills across various projects from AI strategy to client-side deployments, while ensuring architectural decisions are sound and reliable. This role demands a balance of deep technical expertise and strong leadership, focusing on driving innovation, fostering team growth, and building reusable solutions across the organisation. If you're ready to manage high-risk projects and deliver practical, innovative outcomes, this is your chance to shape our future.
What you'll be doing:
- Setting the technical direction for complex ML projects, balancing trade-offs, and guiding team priorities.
- Designing, implementing, and maintaining reliable, scalable ML/software systems and justifying key architectural decisions.
- Defining project problems, developing roadmaps, and overseeing delivery across multiple workstreams in often ill-defined, high-risk environments.
- Driving the development of shared resources and libraries across the organisation and guiding other engineers in contributing to them.
- Leading hiring processes, making informed selection decisions, and mentoring multiple individuals to foster team growth.
- Proactively developing and executing recommendations for adopting new technologies and changing our ways of working to stay ahead of the competition.
- Acting as a technical expert and coach for customers, accurately estimating large work-streams and defending rationale to stakeholders.
Who we're looking for: You are a technical expert among your peers, capable of going deep on particular topics and demonstrating breadth of knowledge to solve almost any problem. You possess strong Python skills and practical experience operationalising models using frameworks like Scikit-learn, TensorFlow, or PyTorch. You are an expert in at least one major Cloud Solution Provider (e.g., Azure, GCP, AWS) and have led teams to build full-stack web applications. You have hands-on experience with containerisation tools like Docker and orchestration via Kubernetes. You can successfully manage and coach a team of engineers, setting team-wide development goals to improve client delivery. You find novel, clever solutions for project delivery and take ownership for successful project outcomes. You're an excellent communicator who can proactively help customers achieve their goals and guide both technical teams and non-technical stakeholders.
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.
Lead Machine Learning Engineer - Retail in London employer: Faculty AI
At Faculty, we pride ourselves on being at the forefront of AI innovation, empowering our employees to lead transformative projects in a collaborative and intellectually stimulating environment. With benefits like unlimited annual leave, private healthcare, and a strong commitment to diversity and employee growth, we foster a culture where your contributions are valued and your career can flourish. Join us in London, where you will not only shape the future of AI but also enjoy a work-life balance that supports your personal and professional aspirations.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Machine Learning Engineer - Retail in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with Faculty employees on LinkedIn. A personal introduction can make all the difference when applying for that Lead Machine Learning Engineer role.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your projects, especially those involving Python and machine learning frameworks. When you get the chance to chat with Faculty, share your experiences and how you've tackled complex problems.
✨Tip Number 3
Practice makes perfect! Get ready for the technical interviews by brushing up on system design and pair programming. Use platforms like LeetCode or HackerRank to sharpen your coding skills and be prepared to showcase your expertise.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining Faculty and being part of our innovative team.
We think you need these skills to ace Lead Machine Learning Engineer - Retail in London
Some tips for your application 🫡
Show Your Passion for AI:When writing your application, let your enthusiasm for AI shine through! We love candidates who are genuinely excited about the technology and its potential. Share any personal projects or experiences that highlight your passion for machine learning.
Tailor Your Application:Make sure to customise your application 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 be shy about showcasing your relevant expertise!
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and focus on communicating your ideas effectively. Highlight your key achievements and how they relate to the role of Lead Machine Learning Engineer.
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 shows you’re keen to join our team at Faculty!
How to prepare for a job interview at Faculty AI
✨Know Your Tech Inside Out
As a Lead Machine Learning Engineer, you’ll need to demonstrate your deep technical expertise. Brush up on your Python skills and be ready to discuss frameworks like Scikit-learn, TensorFlow, or PyTorch. Prepare to explain your architectural decisions and how they impact project outcomes.
✨Showcase Your Leadership Skills
This role requires strong leadership abilities, so think about examples where you've successfully managed teams or mentored others. Be prepared to discuss how you set development goals and foster team growth, as well as how you handle high-risk projects.
✨Prepare for Technical Interviews
Expect a mix of pair programming and system design interviews. Practice coding challenges and system design problems relevant to machine learning. Familiarise yourself with containerisation tools like Docker and orchestration via Kubernetes, as these will likely come up in discussions.
✨Understand the Business Impact
Faculty is all about delivering responsible AI that makes a difference. Be ready to discuss how your work can transform businesses in retail and beyond. Think about past projects where you’ve driven innovation and delivered practical outcomes, and be prepared to share those stories.
