At a Glance
- Tasks: Lead innovative AI projects and guide technical direction for machine learning systems.
- Company: Dynamic retail tech company focused on cutting-edge AI solutions.
- Benefits: Unlimited annual leave, private healthcare, flexible working, and coaching support.
- Other info: Join a diverse team with a strong focus on growth and collaboration.
- Why this job: Make a real impact in AI while leading a talented team and driving innovation.
- Qualifications: Expertise in Python, cloud solutions, and experience with ML frameworks like TensorFlow.
The predicted salary is between 70000 - 90000 £ per year.
Lead Machine Learning Engineer responsible for technical direction and delivery of complex, innovative AI projects. Act as a technical expert across projects from AI strategy to client-side deployments, ensuring architectural decisions are sound and reliable. Balance deep technical expertise with strong leadership, driving innovation, fostering team growth, and building reusable solutions across the organisation.
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 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
- Technical expert among peers, capable of deep expertise and demonstrating breadth of knowledge to solve almost any problem.
- Strong Python skills and practical experience operationalising models using frameworks such as Scikit‑learn, TensorFlow, or PyTorch.
- Expertise in at least one major Cloud Solution Provider (e.g., Azure, GCP, AWS) and experience building full‑stack web applications.
- Hands‑on experience with containerisation tools like Docker and orchestration via Kubernetes.
- Ability to manage and coach a team of engineers, setting team‑wide development goals to improve client delivery.
- Creative problem‑solving and ownership of successful project outcomes.
- Excellent communication skills, guiding technical teams and non‑technical stakeholders to achieve customer goals.
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)
Benefits
- Unlimited Annual Leave Policy
- Private healthcare and dental
- Enhanced parental leave
- Family‑Friendly Flexibility & Flexible working
- Sanctus Coaching
- Hybrid Working
We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Lead Machine Learning Engineer - Retail employer: Faculty
As a Lead Machine Learning Engineer in the retail sector, you will thrive in an innovative environment that champions technical excellence and fosters personal growth. With benefits like unlimited annual leave, private healthcare, and a commitment to family-friendly flexibility, our culture prioritises work-life balance while empowering you to lead cutting-edge AI projects. Join us to not only advance your career but also contribute to meaningful solutions that shape the future of retail.
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We think you need these skills to ace Lead Machine Learning Engineer - Retail
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
