Machine Learning Manager

London
1 week ago
Create job alert

Job Title: Machine Learning Manager
Location: London, United Kingdom (Hybrid)
Employment Type: Full-time, Permanent
Salary: £100,000 - £115,000 per annum

About the Company:

Our client is a rapidly growing fintech company that is transforming the financial sector through innovative AI-powered solutions. They specialise in providing data-driven insights, risk management tools, and automated financial services to clients across banking, payments, and investment sectors.

Role Overview:

We are seeking a highly skilled and motivated Machine Learning Manager to lead a dynamic team of data scientists and machine learning engineers. You will be responsible for driving the development and deployment of ML models that enhance business processes, improve customer experiences, and deliver measurable impact. As a leader, you will work closely with product, engineering, and business teams to ensure the seamless integration of AI solutions into the company’s fintech products.

Key Responsibilities:

  • Lead and mentor a team of machine learning engineers and data scientists.

  • Foster a culture of innovation, collaboration, and continuous learning.

  • Establish best practices for model development, deployment, and monitoring.

  • Define and execute the company’s machine learning strategy in line with business goals.

  • Identify new opportunities where AI/ML can drive business value and improve customer experience.

  • Design, build, and optimise machine learning models for predictive analytics.

  • Collaborate with product managers, data engineers, and business stakeholders to align ML initiatives with business objectives.

  • Communicate complex technical concepts effectively to non-technical stakeholders.

  • Ensure the timely delivery of high-quality AI solutions.

    Required Skills & Experience:

  • Strong knowledge of machine learning algorithms, statistical modelling, and deep learning techniques.

  • Hands-on experience with Python, SQL, PyTorch, Scikit-learn, and other ML frameworks.

  • Proficiency in working with cloud platforms (AWS, Azure, or GCP) and MLOps tools.

  • Experience with model versioning, deployment, and monitoring in production environments.

  • Proven experience managing and mentoring a high-performing ML team.

  • Passion for staying ahead of ML trends and applying innovations to improve products.

  • Strong analytical and problem-solving abilities with a results-oriented mindset.

    If you’re excited about driving innovation in machine learning and want to be part of a collaborative, fast-paced environment where your work makes a real difference, we’d love to hear from you

Related Jobs

View all jobs

Machine Learning Manager

Machine Learning & Data Scientist

Machine Learning & Data Scientist

Machine Learning Engineer

Senior Customer Success Manager at Mobile Ad Tech (Gaming Apps)

Applied Science Manager, Alexa Conversational Modeling & Learning

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.