Head of Artificial Intelligence

UMATR
London
1 month ago
Applications closed

Related Jobs

View all jobs

Head of Artificial Intelligence – Smart Manufacturing

Machine Learning Engineer

Head of Commercial Analysis and Reporting

Head of Hardware

Head of Software Engineering | £150k – Java, Machine Learning, and Data-Driven Innovation

Head of Data Science and Analytics

Important Info

This role is a hybrid working opportunity for candidates based in the UK. You must be willing to travel to a London based office on a weekley basis. This is an experienced hire so please only apply is you have relevant commercial experience.


Company

UMATR has partnered with a cutting edge, high-growth financial services scale-up who are looking to hire a AI Lead to define and implement an AI strategy across the business whilst growing a team of Machine Learning Engineers.


Role

In this position you will develop, lead and drive the execution of the artificial intelligence strategy, specializing in generative AI. You will play a key role in elevating the organistaions generative AI capabilities to new heights. Specifically enhancing their suite of uniquely designed AI services.


Responsibilities

  • Assisit in the design of advanced architectures that integrate AI and ML for predictive analytics, real-time data-driven decision-making and action execution.
  • Build cross-functional teams to incorporate AI seamlessly across our platform and services.
  • Define and implement scalable AI solutions tailored to business needs, ensuring high accuracy and efficiency. Enhance models with the latest AI research, using tools like Git and DVC for version control and collaboration.
  • Driven integration of AI models into production environments, ensuring seamless interaction with existing systems and workflows. Design and implement robust data pipelines to feed AI models with high-quality, real-time data. Ensure model predictions and outputs are reliable, actionable, and accessible.


Key Skills

  • Strong skills in artificial intelligence, especially in generative AI and LLMs.
  • Experience leading and growing teams
  • Deep understanding on GenAI and up to date knowledge of the ever changing landscape
  • Interest in NLP and Knowledge graphs
  • Experience in FS, Trading or Crypto is highly advantageous


The above information is only a preview of the company and role, please contact Jack Calvin to discuss further details. If your profile matches the requirements please apply with your CV attached.

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.

Jobs

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Jobs Careers

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Jobs

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. 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.