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- Tasks: Lead the development of AI in cutting-edge robotics, shaping intelligent behaviours.
- Company: Join a pioneering start-up revolutionising mobile robotic systems with advanced AI.
- Benefits: Enjoy hybrid working, flexible hours, and the chance to work with top talent.
- Why this job: Be at the forefront of AI innovation, making a real-world impact in robotics.
- Qualifications: Strong background in applied AI/ML, multimodal models, and real-world deployment experience required.
- Other info: Work closely with leading roboticists and diverse teams in a fast-paced environment.
The predicted salary is between 54000 - 84000 ÂŁ per year.
We're supporting one of our clients on an exciting search for a ground-breaking start-up robotics company building a new category of intelligent, mobile systems! Reporting into one of the world's leading Roboticists, you’ll be joining at a pivotal moment, working alongside specialist teams across hardware, autonomy, software, and controls to scale how the system learns and performs. Unlike conventional robotic approaches that are bound by limited onboard compute, this platform is designed to shift heavier AI workloads to local infrastructure—opening up possibilities to build far richer, more capable intelligent behaviours.
This is a unique opportunity to help build a dedicated AI function focused on embedding cutting-edge multimodal learning models into next-gen robotic platforms. The role will involve defining the long-term roadmap for how intelligence is deployed across the stack, from perception through to action—combining visual understanding, decision-making, and control into unified, responsive behaviours.
To be successful in this role, you’ll need to bring:
- Strong technical leadership across applied AI/ML, with deep hands-on experience in robotic learning or embodied intelligence
- A solid background in multimodal model development—especially in areas that combine computer vision, language understanding, and interactive learning (LLM, VLM or VLA)
- Real-world deployment experience of learning-based systems, ideally within robotic or physical environments (embodied systems (AI) & reinforcement learning)
- Comfort collaborating across functions, especially with engineering, hardware, and system design teams
- Solid programming and prototyping skills using modern deep learning frameworks (e.g. PyTorch, TensorFlow, JAX)
Location: London (hybrid, with 4 days onsite and flexible hours)
This is a high-impact role for someone who thrives on building ambitious technology in a fast-paced environment—ideal for a technically curious, hands-on leader who wants to shape the future of machine intelligence in the physical world and work with some of the best Robotics talent in the world.
If you meet the requirements above, please apply and one of our team will get back to you with next steps.
Head of Applied AI employer: Acquired Talent Ltd.
Contact Detail:
Acquired Talent Ltd. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Applied AI
✨Tip Number 1
Network with professionals in the robotics and AI fields. Attend industry conferences, webinars, or local meetups to connect with experts and learn about the latest trends. This can help you gain insights into what companies like ours are looking for in candidates.
✨Tip Number 2
Showcase your hands-on experience with applied AI and robotics through personal projects or contributions to open-source initiatives. Having tangible examples of your work can set you apart and demonstrate your technical leadership capabilities.
✨Tip Number 3
Familiarise yourself with the specific technologies and frameworks mentioned in the job description, such as PyTorch and TensorFlow. Being able to discuss your experience with these tools in detail during interviews will highlight your suitability for the role.
✨Tip Number 4
Prepare to discuss your vision for the future of embodied AI and how you would approach building a dedicated AI function. Articulating your ideas clearly can demonstrate your strategic thinking and alignment with our company's goals.
We think you need these skills to ace Head of Applied AI
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your strong technical leadership in applied AI/ML and any hands-on experience you have in robotic learning or embodied intelligence. Use specific examples to demonstrate your skills in multimodal model development.
Craft a Compelling Cover Letter: In your cover letter, express your passion for robotics and AI. Discuss how your background aligns with the role's requirements, particularly your experience with computer vision, language understanding, and interactive learning.
Showcase Relevant Projects: Include details of any real-world deployment experience you have with learning-based systems, especially in robotic or physical environments. Highlight projects where you collaborated with engineering, hardware, or system design teams.
Proofread and Edit: Before submitting your application, carefully proofread your documents for any errors. Ensure that your writing is clear and professional, as this reflects your attention to detail and communication skills.
How to prepare for a job interview at Acquired Talent Ltd.
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with applied AI and machine learning, particularly in robotics. Highlight specific projects where you've successfully implemented multimodal models or reinforcement learning techniques.
✨Demonstrate Collaborative Skills
Since the role involves working closely with engineering and hardware teams, be ready to share examples of how you've effectively collaborated across different functions. This could include joint projects or problem-solving scenarios.
✨Prepare for Technical Questions
Expect in-depth technical questions related to deep learning frameworks like PyTorch or TensorFlow. Brush up on your knowledge of these tools and be ready to discuss your programming and prototyping skills in detail.
✨Articulate Your Vision for AI in Robotics
Think about the long-term roadmap for deploying intelligence in robotic systems. Be prepared to articulate your vision and how you would approach integrating perception, decision-making, and control into unified behaviours.
