Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and deploy cutting-edge machine learning models in a fast-paced financial services 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 familiarity with cloud platforms.
- Other info: Collaborative team environment with opportunities to enhance your skills in MLOps.
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 Portsmouth employer: Edison Smart®
Contact Detail:
Edison Smart® Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Portsmouth
✨Tip Number 1
Network like a pro! Reach out to your connections in the financial services sector and let them know you're on the lookout for a Machine Learning Engineer role. You never know who might have the inside scoop on opportunities that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to financial services. This will give potential employers a taste of what you can do and set you apart from the competition.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with ML libraries and cloud platforms, as well as how you've tackled challenges in previous roles. Practice makes perfect!
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find and apply for roles that match your skills. Plus, you'll be part of a community that values collaboration and growth in the tech space.
We think you need these skills to ace Machine Learning Engineer in Portsmouth
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience in deploying ML models, especially in regulated environments like Financial Services. We want to see how your skills align with our needs!
Showcase Your Projects: Include specific projects where you've designed and built ML systems. We love seeing real-world applications of your work, so don’t hold back on the details about the challenges you faced and how you overcame them.
Highlight Collaboration Skills: Since this role involves working closely with Data Scientists and Software Engineers, make sure to mention any collaborative projects. We value teamwork, so let us know how you’ve contributed to successful outcomes in a team setting.
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 shows you’re keen on joining our team!
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 Collaboration Skills
This role involves working closely with various teams, so be prepared to talk about your collaborative experiences. Share specific instances where you’ve worked with Data Scientists or Software Engineers to build and maintain ML pipelines.
✨Demonstrate Robust Engineering Practices
Highlight your understanding of model governance and best practices in MLOps. Discuss how you ensure performance, resilience, and explainability in your models, as these are crucial in a regulated environment.
✨Familiarity with Tools is Key
If you have experience with tools like Docker, Kubernetes, or MLOps platforms, make sure to mention it. Being able to discuss how you've used these tools in past projects can set you apart from other candidates.
