Head of Engineering (Python)

XCEDE Recruitment Solutions
London
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Technical Services Engineer

Senior Software Developer

Head of Software Engineering (Java)

Head of Software Development

Data Engineer

Advanced Computing Specialist

Head of Engineering - MedTech Start-UpWe are a London based AI MedTech start-up company leveraging computer vision to transform the medical industry. Our mission is to deliver innovative solutions that drive efficiency, accuracy, and scalability to save stakeholders at all levels, time and money.Role Overview

Is this your next job Read the full description below to find out, and do not hesitate to make an application.As the Head of Engineering, you will lead a talented and dynamic engineering team to drive the development and delivery of world-class AI-powered solutions. This is a unique opportunity to shape the technical strategy of a fast-growing organisation, blending strategic leadership with hands-on technical contributions to ensure the success of our platform and solutions.Key ResponsibilitiesDefine and execute the engineering vision, ensuring alignment with the company's broader goals and objectives.Lead, mentor, and grow a team of engineers across various disciplines, fostering a collaborative and high-performance culture.Oversee the development lifecycle of core products, from ideation to deployment, ensuring scalability, security, and reliability.Provide technical expertise, contributing to key architectural decisions and occasionally rolling up your sleeves to solve complex challenges.Stay ahead of technological trends, identifying opportunities for innovation and ensuring our tech stack remains modern and competitive.Partner with cross-functional teams, including product, data science, and operations, to deliver exceptional solutions to clients.Establish and optimise engineering processes, tools, and best practices to enhance productivity and quality.What We're Looking ForProven track record as an engineering leader, ideally in a tech-forward, product-driven company.Strong background in Python software development, architecture, and system design, with a preference for experience in AI, machine learning, or data-intensive platforms.Demonstrated ability to inspire and guide engineering teams, with a focus on fostering a culture of innovation, collaboration, and accountability.Hands-on approach to solving complex technical challenges and implementing practical, scalable solutions.Excellent interpersonal skills, capable of articulating technical concepts to both technical and non-technical stakeholders.Degree in Computer Science, Engineering, or a related field, or equivalent professional experience.Why Join Us?Be at the forefront of innovation in a high-growth industry.Lead and shape the future of a talented engineering team.Work on challenging and impactful projects that make a difference.Enjoy a collaborative, flexible, and inclusive work environment.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Tips for Staying Inspired: How Machine Learning Pros Fuel Creativity and Innovation

Machine learning (ML) continues to reshape industries—from personalised e-commerce recommendations and autonomous vehicles to advanced healthcare diagnostics and predictive maintenance in manufacturing. Yet behind every revolutionary model lies a challenging and sometimes repetitive process: data cleaning, hyperparameter tuning, infrastructure management, stakeholder communications, and constant performance monitoring. It’s no wonder many ML professionals can experience creative fatigue or get stuck in the daily grind. So, how do machine learning experts keep their spark alive and continually generate fresh ideas? Below, you’ll find ten actionable strategies that successful ML engineers, data scientists, and research scientists use to stay innovative and push boundaries. Whether you’re an experienced practitioner or just breaking into the field, these tips can help you fuel creativity and discover new angles for solving complex problems.

Careers

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Careers

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.

🍪 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.