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- Tasks: Lead innovative AI projects and guide teams to deliver impactful solutions.
- Company: Join Faculty, a leader in responsible AI with a focus on real-world impact.
- Benefits: Enjoy unlimited leave, private healthcare, and flexible working arrangements.
- Why this job: Shape the future of AI while working with diverse clients across various industries.
- Qualifications: Expertise in Python, cloud solutions, and experience in leading engineering teams.
- Other info: Diverse and inclusive culture that values intellectual curiosity and positive impact.
The predicted salary is between 48000 - 72000 £ 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: 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 firms 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 meaningful innovation and are proud to set the gold-standard for marrying technical excellence with safe deployment.
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 (2 days in our Old Street office, London)
If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please do apply or reach out to our Talent Acquisition team for a confidential chat - talent@faculty.ai. Please know we are open to conversations about part-time roles or condensed hours.
Lead Machine Learning Engineer in London employer: Faculty
Contact Detail:
Faculty Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Machine Learning Engineer 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 you're applying for that Lead Machine Learning Engineer role.
✨Tip Number 2
Prepare for those interviews! Brush up on your Python skills and be ready to discuss your experience with frameworks like TensorFlow or PyTorch. Practising common interview questions can help you feel more confident and ready to impress.
✨Tip Number 3
Showcase your projects! Whether it's through a portfolio or GitHub, having tangible examples of your work can really set you apart. Highlight any innovative solutions you've developed, especially those that align with Faculty's focus on responsible AI.
✨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 contributing to our mission of impactful AI.
We think you need these skills to ace Lead Machine Learning Engineer 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.
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 relevant projects or achievements!
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. A well-structured application makes it easier for us to see your potential.
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!
How to prepare for a job interview at Faculty
✨Know Your Tech Inside Out
As a Lead Machine Learning Engineer, you’ll need to showcase 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.
✨Demonstrate Leadership Skills
This role requires strong leadership abilities, so think about examples where you've successfully managed teams or projects. Be prepared to discuss how you set development goals and foster team growth. Highlight your experience in mentoring others and making informed hiring decisions.
✨Prepare for Technical Challenges
Expect to face technical challenges during the interview, especially in the pair programming and system design interviews. Practice coding problems and system design scenarios relevant to machine learning projects. Show your problem-solving skills and ability to think on your feet.
✨Communicate Effectively
Excellent communication is key, especially when guiding both technical teams and non-technical stakeholders. Practice explaining complex concepts in simple terms. Be ready to discuss how you’ve helped customers achieve their goals and how you can bridge the gap between tech and business.
