Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Principal Machine Learning Engineer - Team Lead

Qodea
Manchester
8 months ago
Applications closed

Related Jobs

View all jobs

Senior/ Principal Data Engineering Consultant- London

Principal MLOps Machine Learning Operations Developer for AI Research

Engineering Manager, Machine Learning Platform

Lead Data Engineer, Machine Learning

Data Scientist - Ad Campaign Performance

Senior Data Engineer

As a Principal Machine Learning Engineer for Qodea, Europe's largest dedicated Google Cloud partner, you will lead the design and delivery of Machine Learning solutions for clients in addition to performing line management duties for a team of ML Engineers and Data Scientists. You'll report into the Head of Data & AI.

You’ll develop and deploy innovative machine learning models and AI solutions on Google Cloud using frameworks such as TensorFlow, scikit-learn and torch. You’ll use your hands-on experience of developing, training and deploying AI models to help customers activate their data. 

You’ll draw upon your technical expertise and track record of delivery to have positive and meaningful engagements with customers, to help them understand what’s achievable with Google Cloud products and services.  You’ll be able to communicate concepts to both technical and non-technical audiences. 

Your solution designs will always consider the customers’ requirements, and will be scalable and supportable. You’ll always be open to exploring new technologies in this fast-moving field and will foster an innovative and creative mindset among the wider ML Team.

Your Line Management duties will consist of regularly engaging with your team members, enabling their professional development and being a consistent source of encouragement and support during their time with the organisation. You'll also foster a positive and collaborative environment within the Machine Learning team through remote and in-person meetups, social events and knowledge-sharing activities.

Responsibilities:

  • Lead discussions with clients to understand their business problems, work with your team to design technical solutions using machine learning models
  • Develop and deploy machine learning models on Google Cloud
  • Use version control and agile working practices
  • Stay up-to-date with the latest developments in machine learning and bring new ideas to the team.

Requirements

  • Experience as a technical lead on technical projects, ideally involving a public cloud provider
  • Experience with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP).
  • Strong grasp of statistics and probability fundamentals
  • Solid understanding of machine learning algorithms for supervised and unsupervised learning
  • Hands on experience training, deploying and optimising ML models
  • Strong Python and SQL skills
  • Experience with Cloud ML tools
  • Collaborative, proactive, logical, methodical, and attentive to detail
  • Passion for machine learning and demonstrating your ability to keep updated on the latest advancements in the industry.

About Qodea

Qodea (formally Appsbroker CTS) is the largest Google Cloud-only digital consultancy in Europe. Our name marks the culmination of a journey which began with the merger of Appsbroker and CTS in 2023. Combining the words ‘code’ and ‘idea’, our name embodies the essence of who we are and what we do; providing tried and trusted digital solutions, whilst helping our clients look to the future and innovate.

As a purpose-driven, certified B Corp, we strive to be great to work with and great to work for. We’re lucky to have some fantastic household names as customers, and fantastic colleagues delivering the ideas, technologies, and impacts that matter.

With offices across Europe, you’ll be joining a dynamic team of talented but down-to-earth experts, with a presence across the UK, the Netherlands, Romania, and Belgium. 

By joining forces, both companies bring over 15 years of Google Cloud experience under one roof, with over 420+ Google certifications, a list of brilliant enterprise customers, incredibly talented people, and multiple industry awards - meaning we can be trusted to deliver.

Benefits

  • 36 days off each year including Bank Holidays (and your birthday off)
  • Private healthcare scheme
  • Company pension 
  • Flexible working culture
  • Work from Anywhere policy (up to 90 days per year)
  • 10 paid Learning Days each year in addition to annual leave
  • Company events - opportunities to meet colleagues you don’t see every day
  • Regular opportunities for industry recognised training and certifications
  • Learning and development opportunities
  • Opportunities to develop within a fast growing-tech business with ambitious growth and impact goals

Location:

This role can be either fully remote or hybrid based depending on your preference. We have offices in London, Swindon, Manchester and Edinburgh which you can choose to work from as often as you like. There is no mandatory office working, but you might be expected to travel to offices or customer sites for specific meetings or events.

Diversity and Inclusion Statement

At Qodea, we look after each other in an environment where everyone can work together to achieve great things. We’re proud of our people-first culture that welcomes individuals from all backgrounds. Our commitment to diversity and inclusion creates a dynamic community, unlocks innovation and great ideas, and unites us around a common purpose - and we look for talented people to join us who share these values.

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.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.

Why Now Is the Perfect Time to Launch Your Career in Machine Learning: The UK's Intelligence Revolution

The United Kingdom stands at the epicentre of a machine learning revolution that's fundamentally transforming how we solve problems, deliver services, and unlock insights from data at unprecedented scale. From the AI-powered diagnostic systems revolutionising healthcare in Manchester to the algorithmic trading platforms driving London's financial markets, Britain's embrace of intelligent systems has created an extraordinary demand for skilled machine learning professionals that dramatically exceeds the current talent supply. If you've been seeking a career at the forefront of technological innovation or looking to position yourself in one of the most impactful sectors of the digital economy, machine learning represents an exceptional opportunity. The convergence of abundant data availability, computational power accessibility, advanced algorithmic development, and enterprise AI adoption has created perfect conditions for machine learning career success.