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- Tasks: Lead the development of AI systems and build a top-notch engineering team.
- Company: Join a pioneering tech startup focused on AI and data science innovation.
- Benefits: Enjoy flexible work options and the chance to shape company culture.
- Why this job: Be at the forefront of AI technology and make a real impact in a growing field.
- Qualifications: 7+ years in data science or software engineering, with strong Python and cloud skills.
- Other info: Opportunity to work in a dynamic environment and collaborate with visionary founders.
The predicted salary is between 72000 - 108000 £ per year.
We’re looking for an experienced and entrepreneurial engineer to join as one of our first hires. This is a hands-on leadership role that combines deep data science and AI expertise, robust backend/data infrastructure development, and the opportunity to shape the technical DNA of our company. You’ll lead the buildout of our AI systems and platform, shape our MLOps strategy, and ultimately grow and lead a world-class engineering team.
What You’ll Do:
- Build core data infrastructure, pipelines, and ML systems from scratch using Python (70+%), GCP, AWS, and Kubernetes.
- Research & deploy advanced AI/ML models tailored to real-world use cases.
- Own the full MLOps lifecycle: model development, deployment, monitoring, and iteration.
- Recruit & lead a high-performance team of engineers and data scientists.
- Collaborate closely with the co-founders and advisors to align tech execution with business goals.
- Help define technical culture, standards, and processes as a founding team member.
What We’re Looking For:
- 7+ years of hands-on experience in data science, software engineering, or MLOps.
- Proven ability to ship production-grade AI/ML systems.
- Deep expertise in Python, plus strong experience with data engineering, cloud infrastructure (GCP/AWS), and container orchestration (Kubernetes).
- Past experience in early-stage, high-growth tech companies—ideally in Defence Tech, AI infrastructure, or enterprise SaaS.
- Comfortable operating in high-ambiguity environments and making architecture decisions.
- Based in, or willing to relocate to, London or Europe.
Head of Artificial Intelligence employer: Global M
Contact Detail:
Global M Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Artificial Intelligence
✨Tip Number 1
Network with professionals in the AI and data science fields. Attend industry conferences, webinars, or local meetups to connect with potential colleagues and mentors who can provide insights into the role and company culture.
✨Tip Number 2
Showcase your hands-on experience by discussing specific projects where you've built AI systems or led teams. Be prepared to share examples of how you’ve tackled challenges in MLOps and data infrastructure development.
✨Tip Number 3
Familiarise yourself with the latest trends and technologies in AI and MLOps. Being knowledgeable about tools like GCP, AWS, and Kubernetes will not only help you in discussions but also demonstrate your commitment to staying current in the field.
✨Tip Number 4
Prepare to discuss your leadership style and how you plan to build and nurture a high-performance team. Think about your approach to collaboration and how you can align technical execution with business goals, as this is crucial for the role.
We think you need these skills to ace Head of Artificial Intelligence
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data science, software engineering, and MLOps. Focus on specific projects where you've built AI systems or led teams, especially in high-growth tech environments.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how your background aligns with the company's goals. Mention your experience with Python, GCP, AWS, and Kubernetes, and how you can contribute to shaping their technical culture.
Showcase Relevant Projects: Include examples of past projects that demonstrate your ability to build data infrastructure and deploy AI/ML models. Highlight any leadership roles you've taken on and the impact of your work on previous teams or companies.
Prepare for Technical Questions: Anticipate technical questions related to AI/ML systems, data engineering, and cloud infrastructure during the interview process. Be ready to discuss your decision-making process in high-ambiguity environments and how you've tackled challenges in past roles.
How to prepare for a job interview at Global M
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with Python, GCP, AWS, and Kubernetes. Highlight specific projects where you've built data infrastructure or deployed AI/ML models, as this will demonstrate your capability to lead the technical aspects of the role.
✨Demonstrate Leadership Skills
Since this role involves leading a team, share examples of how you've successfully recruited, mentored, or managed engineers and data scientists in the past. Discuss your approach to building a high-performance team and fostering a positive technical culture.
✨Align Tech with Business Goals
Prepare to discuss how you can align technical execution with business objectives. Think about past experiences where you collaborated with stakeholders to ensure that tech initiatives supported broader company goals, especially in high-growth environments.
✨Embrace Ambiguity
This position requires comfort in high-ambiguity situations. Be ready to share instances where you've made critical architecture decisions without complete information, showcasing your problem-solving skills and adaptability in fast-paced settings.
