At a Glance
- Tasks: Design and develop cutting-edge machine learning solutions in a collaborative team.
- Company: Established financial services organisation investing in data science and AI.
- Benefits: Competitive salary, bonus, flexible hybrid working, and comprehensive benefits.
- Other info: Exciting growth opportunities in a fast-paced, innovative environment.
- Why this job: Join a dynamic team to shape the future of AI and solve real-world challenges.
- Qualifications: Experience in machine learning engineering, strong Python skills, and cloud deployment knowledge.
The predicted salary is between 80000 - 98000 £ per year.
Location: Flexible (Hybrid)
Working set up: Hybrid
Salary: Competitive + bonus + benefits
SPG are working on behalf of an established financial services organisation investing heavily in its data science and AI capabilities. As part of an expanding team, the business is delivering a range of greenfield machine learning and generative AI initiatives designed to solve real-world business challenges and enhance customer outcomes.
This is an exciting opportunity to join a collaborative data function where you'll help shape the organisation's machine learning engineering capability while building scalable, production-ready AI solutions.
The Role
Working as part of a cross-functional Data Science team, the Machine Learning Engineer will play a key role in taking machine learning models from research through to production. You'll work closely with Data Scientists, Data Engineers and Software Engineers to build robust, scalable ML solutions while helping define best practices, tooling and automation across the full machine learning lifecycle. This role is ideal for someone with a passion for software engineering, cloud technologies and productionising machine learning solutions within an enterprise environment.
Key responsibilities
- Design, develop and enhance the organisation's machine learning engineering capability and Data Science platform
- Build and automate end-to-end machine learning workflows using CI/CD and Infrastructure as Code
- Collaborate with Data Scientists throughout the model development and deployment lifecycle
- Work closely with engineering teams and business stakeholders to deliver production-ready AI solutions
- Develop high-quality, maintainable Python code following software engineering best practices
- Contribute to technical design decisions including model deployment strategies and solution architecture
- Support the deployment and operationalisation of both traditional machine learning and Generative AI solutions
- Help establish engineering standards, tooling and best practices as the function continues to grow
Required skills and experience
- Commercial experience in Machine Learning Engineering or Data Science within a production environment
- Strong Python development skills with a solid understanding of software engineering best practices
- Experience deploying machine learning solutions into cloud-native production environments
- Experience with containerisation technologies such as Docker and orchestration platforms including Kubernetes
- Knowledge of modern MLOps practices including CI/CD, version control (Git) and infrastructure automation
- Experience working with cloud platforms and modern data ecosystems (Azure and Databricks experience beneficial)
- Strong understanding of machine learning principles and model deployment processes
- Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders
- Experience working with Agile delivery methodologies and tools such as Azure DevOps and Jira
Desirable experience
- Experience working with Large Language Models (LLMs), Generative AI or Agentic AI solutions in a commercial environment
- Experience deploying machine learning models within regulated industries such as financial services or insurance
- Exposure to enterprise-scale MLOps and cloud infrastructure
- Experience contributing to platform architecture and engineering best practices
Machine Learning Engineer in Manchester employer: SPG Resourcing
SPG Resourcing is an excellent employer that fosters a collaborative and inclusive work culture, making it an ideal place for HR Data & Systems Analysts to thrive. With a strong focus on employee growth, the company offers comprehensive benefits such as annual bonuses, a generous 12% employer pension contribution, and private medical insurance, all while working in vibrant cities like Manchester or Leeds. Join us to be part of meaningful global payroll projects and enhance your career in a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer in Manchester
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like SPG Resourcing!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Machine Learning Engineer at SPG Resourcing.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like SPG Resourcing.
✨Apply Directly through Our Website
When you find a suitable opening like Machine Learning Engineer at SPG Resourcing, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Machine Learning Engineer in Manchester
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at SPG Resourcing, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at SPG Resourcing. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at SPG Resourcing
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at SPG Resourcing!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
