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Lead Machine Learning EngineerFaculty • London
Lead Machine Learning Engineer

Lead Machine Learning Engineer

Faculty • London
30+ days ago
Job type
  • Part-time
Job description

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.

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Lead Machine Learning Engineer • London

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