At a Glance
- Tasks: Design and build production-grade machine learning applications for financial services.
- Company: Leading AI consultancy with a focus on innovative solutions.
- Benefits: Competitive salary, bonus, hybrid work, and opportunities for mentorship.
- Other info: Join a dynamic team with a culture of engineering excellence.
- Why this job: Make a real impact by deploying high-stakes AI systems in finance.
- Qualifications: Expert Python skills and experience in production machine learning systems.
The predicted salary is between 90000 - 110000 £ per year.
We're partnering with a leading AI consultancy that has spent over a decade helping some of the world's most sophisticated organisations deploy machine learning and AI into production. Their Financial Services practice is experiencing significant growth and is looking for a Senior Machine Learning Engineer to help deliver large-scale AI systems across banking, insurance, asset management and broader financial markets.
This is not a research or data science role. We're looking for engineers who understand that successful AI products are built on strong software engineering foundations. The ideal candidate will combine deep machine learning expertise with a proven track record of building reliable, scalable production systems within regulated financial environments.
You'll work directly with clients to design and deploy production-grade AI solutions that solve commercially critical problems, operating at the intersection of machine learning, software engineering, cloud infrastructure and financial services.
What You'll Be Doing
- Designing and building production-grade machine learning applications and platforms
- Developing scalable software systems that enable AI products to operate reliably in highly regulated environments
- Leading technical architecture discussions and influencing engineering best practices
- Working closely with stakeholders across technology, product and commercial functions
- Translating complex business challenges into robust AI-powered solutions
- Mentoring engineers and contributing to a culture of engineering excellence
What We're Looking For
- Strong software engineering background with expert-level Python development experience
- Experience building, deploying and maintaining production machine learning systems
- Proven track record operating within financial services, fintech, banking, insurance or capital markets environments
- Deep understanding of cloud-native architectures and modern engineering practices
- Hands-on experience with containers, Kubernetes and scalable distributed systems
- Ability to engage confidently with both technical teams and senior business stakeholders
Why This Role?
The most successful machine learning systems in financial services are rarely won by better models alone. They're won by engineers who can combine software engineering rigour, machine learning expertise and a strong understanding of the operational realities of regulated financial environments. If you've built production systems, understand the demands of financial services, and want to work on high-impact AI deployments rather than endless proofs of concept, we'd love to hear from you.
Machine Learning Engineer in Slough employer: Omnis Partners
Join a leading AI consultancy in London that champions innovation and excellence in the financial services sector. With a strong focus on employee growth, you will have the opportunity to work on impactful AI projects while collaborating with top-tier clients. The hybrid work model promotes a healthy work-life balance, and the culture of mentorship ensures that your skills as a Machine Learning Engineer will flourish in this dynamic environment.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer in Slough
✨Tip Number 1
Network like a pro! Reach out to your connections in the financial services and AI sectors. Attend meetups, webinars, or industry events to meet potential employers and get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects and production systems. This will give you an edge when discussing your experience with hiring managers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and software engineering principles. Be ready to discuss your past projects and how you've tackled challenges in regulated environments.
✨Tip Number 4
Don't forget to apply through our website! We have loads of opportunities that might be perfect for you. Plus, it shows you're serious about joining our team!
We think you need these skills to ace Machine Learning Engineer in Slough
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your software engineering skills and experience with machine learning systems. We want to see how you've built reliable, scalable solutions in financial services, so don’t hold back on those details!
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. Talk about your experience in regulated environments and how you’ve tackled complex business challenges with AI solutions.
Showcase Your Projects:If you've worked on any relevant projects, make sure to include them! We love seeing real-world applications of your skills, especially if they involve cloud-native architectures or scalable distributed systems.
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 this exciting opportunity. Don’t miss out!
How to prepare for a job interview at Omnis Partners
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, cloud-native architectures, and Kubernetes. Brush up on your experience with scalable distributed systems, as you'll likely be asked to discuss how you've implemented these in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex business challenges using machine learning solutions. Think about how you translated those challenges into robust AI applications, and be ready to explain your thought process and the impact of your work.
✨Engage with Stakeholders
Since this role involves working closely with both technical teams and senior business stakeholders, practice articulating technical concepts in a way that non-technical people can understand. This will demonstrate your ability to bridge the gap between engineering and business needs.
✨Emphasise Your Mentoring Experience
If you have experience mentoring other engineers, be sure to highlight this during the interview. Discuss how you’ve contributed to a culture of engineering excellence and how you can bring that mindset to the new team. It shows leadership potential and a commitment to team growth.
