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For Companies At a Glance
- Tasks: Design and deploy cutting-edge machine learning models in a fast-paced financial environment.
- Company: Join a leading financial services organisation with a focus on innovation.
- Benefits: Competitive daily rate, remote work flexibility, and potential for contract extension.
- Why this job: Make an impact by working on high-volume ML systems that drive real-world results.
- Qualifications: Proven experience in machine learning, strong Python skills, and cloud platform familiarity.
- Other info: Collaborative team environment with opportunities for professional growth.
We’re seeking an experienced Machine Learning Engineer to support a Financial Services organisation on an initial 6-month contract, working on production-grade ML systems that operate in regulated, high-volume environments. This role is ideal for someone comfortable taking models from research through to deployment, with a strong appreciation for robust engineering, governance, and scalability.
Responsibilities
- Design, build, and deploy machine learning models into production within a Financial Services environment
- Collaborate closely with Data Scientists, Software Engineers, Risk, and Product teams
- Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring)
- Ensure models meet requirements around performance, resilience, and explainability
- Contribute to MLOps best practices, model governance, and technical standards
- Support model monitoring, drift detection, and ongoing optimisation
Required Experience
- Proven commercial experience as a Machine Learning Engineer, ideally within Financial Services, FinTech, or a regulated environment
- Strong Python skills and hands-on experience with ML libraries (TensorFlow, PyTorch, scikit-learn)
- Experience deploying and supporting ML models in production
- Solid understanding of data pipelines, versioning, testing, and software engineering best practices
- Experience working with cloud platforms (AWS, GCP, or Azure)
Nice to Have
- Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases
- Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.)
- Docker and Kubernetes experience
- Exposure to model governance, explainability, or regulatory frameworks
Contract Details
- £650–£750 per day (Outside IR35)
- Initial 6-month contract, with strong extension potential
- Immediate or short-notice start preferred
Machine Learning Engineer in Sheffield employer: Edison Smart®
Contact Detail:
Edison Smart® Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Sheffield
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even online forums. The more people you know, the better your chances of landing that Machine Learning Engineer gig.
✨Show Off Your Skills
Create a portfolio showcasing your projects and experience with ML models. Whether it's a GitHub repo or a personal website, let your work speak for itself. This is your chance to shine and show potential employers what you can do!
✨Ace the Interview
Prepare for technical interviews by brushing up on your Python skills and ML concepts. Practice common interview questions and be ready to discuss your past projects in detail. Confidence is key, so walk in ready to impress!
✨Apply Through Us!
Don’t forget to check out our website for the latest job openings. Applying through StudySmarter gives you an edge, as we’re always looking to connect talented individuals with great opportunities in the financial services sector.
We think you need these skills to ace Machine Learning Engineer in Sheffield
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Machine Learning Engineer, especially in Financial Services. We want to see how your skills align with the job description, so don’t be shy about showcasing relevant projects and achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for this role. We love seeing enthusiasm and a clear understanding of the responsibilities, so make it personal and engaging.
Showcase Your Technical Skills: Since we’re looking for someone with strong Python skills and experience with ML libraries, make sure to mention specific projects where you’ve used these technologies. We want to know how you’ve tackled challenges in deploying ML models!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts and submit your materials!
How to prepare for a job interview at Edison Smart®
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts, especially those relevant to financial services. Be ready to discuss your experience with ML libraries like TensorFlow and PyTorch, and have examples of models you've deployed in production.
✨Showcase Your Collaboration Skills
This role involves working closely with various teams, so be prepared to talk about how you've collaborated with Data Scientists, Software Engineers, and other stakeholders in the past. Highlight any successful projects where teamwork made a difference.
✨Demonstrate Your Engineering Mindset
Since robust engineering and scalability are key, come equipped with examples of how you've built and maintained end-to-end ML pipelines. Discuss your approach to model governance and MLOps best practices to show you're serious about quality.
✨Be Ready for Technical Questions
Expect some deep dives into your technical skills, especially around data pipelines and cloud platforms. Brush up on your knowledge of AWS, GCP, or Azure, and be ready to explain how you've used these tools in your previous roles.