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- Tasks: Build and optimise AI systems to enhance predictive automation capabilities.
- Company: Join Vanguard, a revolutionary investment company focused on client interests.
- Benefits: Enjoy a hybrid work model, competitive salary, and a commitment to diversity.
- Why this job: Make a real impact by developing cutting-edge machine learning solutions.
- Qualifications: Strong programming skills in Python and experience with ML frameworks.
- Other info: Collaborative environment with excellent career growth opportunities.
The predicted salary is between 36000 - 60000 £ per year.
The Chief Data & Analytics Office (CDAO) is looking for a Machine Learning Engineer to build efficient, data-driven AI systems that advance our predictive automation capabilities. You should be highly skilled in statistics and programming, with the ability to confidently assess, analyse, and organise large amounts of data. You should also be able to execute tests and optimise Vanguard’s machine learning models and algorithms. You will play a critical role in designing and developing machine learning algorithms and AI applications and systems for Vanguard, solving complex problems with multilayered data sets and optimising existing machine learning libraries and frameworks. You will collaborate with data scientists, data analysts, data engineers, and data architects on production systems and applications, and identify differences in data distribution that could potentially affect model performance in real-world applications.
What will you be doing? You will be a major contributor in our GenAI intake process, assessing and reviewing use cases from around the business, and play a key role in Vanguard’s model governance processes. In addition, you will:
- Design, build, and productionise machine learning and GenAI solutions, ensuring they meet scalability, reliability, and performance requirements for enterprise use.
- Partner with data scientists to translate experimental models into robust, well-engineered systems ready for deployment in production environments.
- Develop and maintain ML pipelines including feature engineering, model training, evaluation, versioning, monitoring, and automated retraining workflows.
- Enhance our MLOps capabilities by contributing to CI/CD pipelines, infrastructure automation, model registries, and containerised deployment frameworks.
- Conduct thorough model evaluation, including benchmarking, drift detection, fairness analysis, and performance optimisation to ensure models behave consistently in real-world scenarios.
- Collaborate with data engineers and architects to improve underlying data quality, data flows, and platform capabilities used for ML development.
- Perform advanced experimentation, leveraging modern ML frameworks to prototype new algorithms, assess their viability, and recommend adoption paths.
- Support CDAO governance processes, ensuring models comply with Vanguard’s standards for transparency, risk controls, documentation, and regulatory alignment.
- Advise business teams and product owners, helping shape opportunities for automation, prediction, and GenAI enablement across the organisation.
- Contribute to best practices and reusable ML components, strengthening our internal libraries, frameworks, and engineering standards.
- Stay current with emerging AI trends, evaluating new tools, foundation models, and methodologies to guide strategic adoption within CDAO.
What it takes:
- Programming: Strong proficiency in Python.
- Machine Learning Frameworks: TensorFlow, PyTorch, Scikit-learn.
- Statistics & Mathematics: Advanced knowledge of statistics, probability, and optimisation.
- Model Development & Optimisation: Building, testing, and tuning ML models and algorithms.
- Data Handling: Experience with large, complex datasets; SQL and data preprocessing.
- MLOps & Deployment: Familiarity with CI/CD, Docker, Kubernetes, and cloud platforms (AWS).
- Generative AI & Model Governance: Understanding of GenAI use cases and compliance processes.
Special Factors: Vanguard is not offering sponsorship for this position. This is a hybrid position and would require you to work in the office 3 days per week (Tuesday, Wednesday & Thursday).
Vanguard is an equal opportunity employer. Vanguard is committed to providing all crew members a working environment that is free from discrimination, prejudice and bias.
Machine Learning Engineer in Manchester employer: Vanguard Group, Inc.
Contact Detail:
Vanguard Group, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Manchester
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's GitHub repos or a personal website, having tangible examples of your work can really set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common technical questions and coding challenges. Use platforms like LeetCode or HackerRank to sharpen your skills. The more prepared you are, the more confident you'll feel!
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from candidates who are excited about joining us at Vanguard. Plus, it shows you're genuinely interested in being part of our team.
We think you need these skills to ace Machine Learning Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your programming skills, especially in Python, and any experience with ML frameworks like TensorFlow or PyTorch. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how you can contribute to Vanguard's goals. Be sure to mention any relevant projects or experiences that showcase your skills.
Showcase Your Projects: If you've worked on any machine learning projects, make sure to include them in your application. Whether it's a personal project or something from a previous job, we love seeing practical examples of your work and how you tackle complex problems.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you'll find all the details you need about the role and our company culture there!
How to prepare for a job interview at Vanguard Group, Inc.
✨Know Your Tech Stack
Make sure you’re well-versed in the programming languages and frameworks mentioned in the job description, especially Python, TensorFlow, and PyTorch. Brush up on your statistics and optimisation techniques, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples of how you've tackled complex problems using machine learning. Think about the challenges you faced, the data you worked with, and how you optimised your models. This will demonstrate your ability to apply your skills in real-world scenarios.
✨Understand MLOps and CI/CD
Familiarise yourself with MLOps practices and tools like Docker and Kubernetes. Be ready to explain how you’ve implemented CI/CD pipelines in past projects, as this is crucial for the role. Showing that you can bridge the gap between development and operations will set you apart.
✨Emphasise Collaboration
Since the role involves working closely with data scientists, engineers, and architects, be prepared to discuss your experience in collaborative environments. Highlight any projects where teamwork was key to success, and express your enthusiasm for contributing to a diverse team.
