Head of AI/ML - Robotics start-up

City of London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer (18 Months FTC)

Data Engineer (18 Months FTC)

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Data science programme lead

Data science programme lead

Head of AI/ML - Robotics start-up

Are you ready to revolutionise the world of robotics as a Head of AI?

Do you want to join a growing visionary team that's redefining human-machine collaboration?

Step into a leadership role where your expertise in AI/ML will drive the development of humanoid robots that redefine human-machine collaboration.

We are on a mission to transform how humans and machines work together. Imagine a world where millions of humanoid robots take on tasks that are hazardous, monotonous, or simply undesirable, allowing people to focus on what truly matters.

Our vision is a future of abundance, where technology addresses labor shortages and creates new opportunities for well-being.

As Head of AI/ML, you will:

  • Lead the design and development of AI/ML algorithms for perception, decision-making, control, and autonomous driving.
  • Define and execute research roadmaps, establishing data pipelines to support cutting-edge AI/ML workflows.
  • Integrate AI/ML capabilities into our humanoid platform, driving collaboration with cross-functional teams.
  • Represent our technological advancements in industry forums and foster partnerships with academia and research institutions.
  • Inspire and grow a talented AI/ML team, shaping the future of robotics through innovation and strategic leadership.

    What We're Looking For:
  • Proven experience in AI/ML, particularly within robotics, automation, or autonomous systems.
  • Expertise in machine learning, deep learning, computer vision, NLP, and world model architectures (SLAM, CNN/DNN)
  • Strong leadership skills with the ability to build and nurture high-performing teams.
  • A strategic thinker with excellent communication skills, ready to drive impactful AI/ML initiatives.

    What's in It for You:
  • Competitive salary + stock options.
  • Flexible working hours and a dynamic start-up environment.
  • Be part of a groundbreaking team shaping the future of robotics.

    Offices in London, with relocation opportunities across Europe.
    Sponsorship can be provided.

    Ready to make a difference? Apply now for immediate consideration.

    Piper Maddox is acting as an Employment Agency in relation to this vacancy

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.