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For Companies At a Glance
- 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 competitive salary, flexible working options, and a 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 required.
- 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.
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 cloud infrastructure. Being knowledgeable about tools like GCP, AWS, and Kubernetes will demonstrate your commitment to staying current in the field.
✨Tip Number 4
Prepare to discuss your vision for building a high-performance team. Think about how you would approach recruiting and mentoring engineers and data scientists, as this is a key aspect of 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 the technical culture.
Showcase Relevant Projects: Include a portfolio or a section in your CV that showcases relevant projects. Highlight any advanced AI/ML models you've deployed and the impact they had on previous companies, particularly in Defence Tech or enterprise SaaS.
Prepare for Technical Questions: Anticipate technical questions related to AI/ML systems, data infrastructure, and MLOps. Be ready to discuss your decision-making process in high-ambiguity environments and how you've successfully led teams in the past.
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 of instances where you've collaborated with co-founders or stakeholders to ensure that tech strategies support overall company goals, as this is crucial for a founding team member.
✨Embrace Ambiguity
This role requires comfort in high-ambiguity environments. Be ready to share experiences where you've made critical architecture decisions without clear guidelines. This will show your ability to thrive in dynamic settings and adapt to changing circumstances.
