Chief Technology Officer

numi
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist — Healthcare Analytics & Growth

Senior Data Analyst- Data Extraction, London / Manchester / Belfast

Senior Data Analyst- Data Extraction, London / Manchester / Belfast

Data Engineer II

Lead Data Scientist

Founding AI & Computer Vision Engineer — Equity, Unlimited PTO

‍ CTO– Shape the Future, Lead the Way

❤️ If you believe in Tech For Good. Then this place could be for you

Remote, ideally within a couple of hours time zone to London

Building a phenomenal company culture and workplace

Data, data, data driving global decision making

Basic + stock options, 3rd time Founders

Shape the future


Are You Ready to Build the Future of Scalable Technology and Transformative Data Solutions?

Imagine joining an early-stage company on a mission to redefine how data drives global decision-making. You’re someone who thrives on solving complex technical challenges, building world-class engineering teams, and delivering platforms that scale seamlessly—all while making a lasting impact.

This is your opportunity to lead as CTO in a company at the intersection of data, technology, and innovation. Here, your work will directly shape the future of a cutting-edge platform designed to transform how businesses and industries use data to drive measurable outcomes.


What You’ll Do

•Shape the Technical Vision:Define and implement the company’s technology strategy, ensuring it aligns with long-term business goals.

•Build a Scalable Platform:Develop a robust, automated platform that integrates data pipelines, machine learning, and advanced analytics.

•Foster Innovation:Leverage your expertise to integrate cutting-edge ML models, reduce operational costs, and drive efficiency in data processing.

•Lead and Inspire a High-Performing Team:Build and scale an exceptional engineering team, nurturing a culture of excellence, collaboration, and continuous improvement.

•Drive Outcomes at Scale:Ensure the technology enables customers to make data-driven decisions effectively and efficiently while positioning the company as an industry leader.


You Are:

• Astrategic thinkerwith deep technical expertise in data pipelines, machine learning, and scalable architecture.

• Anexperienced leaderwho has built, scaled, and mentored engineering teams to deliver exceptional outcomes.

• Passionate about solving complex technical problems andexcited to work on projects that drive global impact.

• Collaborative, humble, and eager to engage with non-technical stakeholders, translating technical innovation into meaningful results.


What You Bring

• Proven expertise in full-stack development, includingPython, React, and cloud-native environmentslike AWS or Azure.

• A track record of building scalable, data-intensive platforms and integratingML modelsinto production environments.

• Hands-on experience transitioning from prototype to scalable systems, including automation of workflows.

• Leadership experience in early-stage or high-growth environments, with a focus on team building, technical execution, and long-term strategic planning.


Why This Role?

•Impact at Scale:Your work will directly shape a platform poised to revolutionise how industries utilise data.

•A Collaborative, Mission-Driven Culture:Join a team of smart, motivated individuals united by a shared vision.

•A Rare Opportunity to Build:Lay the foundations for a scalable, high-impact platform while fostering a thriving engineering culture.

•Competitive Compensation and Equity:Reflecting the high stakes and immense potential of your contribution.


Location:Remote-first, ideally within two hours of GMT (or similar European time zones).

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.

Education

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

Careers Jobs

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

🍪 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.