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- Tasks: Design and own ML platforms to streamline pricing workflows and support rapid model deployment.
- Company: Join a leading Audit and Advisory business with a focus on innovation.
- Benefits: Competitive salary, contract length of 12 months, and potential for extension.
- Why this job: Shape cutting-edge pricing technology and collaborate with diverse teams for impactful results.
- Qualifications: Bachelor’s or Master’s in relevant fields and strong ML lifecycle management experience.
- Other info: Dynamic role in London with opportunities for professional growth.
The predicted salary is between 43200 - 72000 £ per year.
G MASS Consulting is supporting a leading Audit and Advisory business. We’re looking for a Machine Learning Engineer to shape and scale their pricing technology. In this role, you’ll design and own ML platforms that streamline pricing workflows, support rapid model deployment, and ensure models perform reliably at scale. Partnering with Data Science, Actuarial, and Product teams.
Responsibilities
- Build and support ML lifecycle tooling for model deployment, monitoring, and alerting
- Maintain and improve the Kubeflow environment for Data Scientists and Actuaries
- Create pricing analytics tools to accelerate impact analysis and reduce manual work
- Collaborate with pricing and product teams to deliver high-impact tooling
- Communicate complex concepts clearly to technical and non-technical audiences
Requirements
- Bachelor’s or Master’s degree in Statistics, Data Science, Computer Science, or a related field
- Strong experience managing the full ML model lifecycle (batch and online)
- Solid understanding of statistical methods, including GLMs and modern ML techniques
- Proven ability to build and deploy production-quality Python applications (pandas, scikit-learn)
- Experience with DevOps and ML tooling, including Kubernetes, Docker, CI/CD, and git-based workflows
- Familiarity with cloud platforms (AWS) and cloud data warehouses (Snowflake/SQL)
Benefits
- Salary: to be discussed, depending on experience
- Length: 12 months, with the view to extend
- Employment Type: Contract
- Seniority Level: Mid-Senior
- Location: London, England, United Kingdom
Senior Machine Learning Engineer in London employer: G MASS Consulting
Contact Detail:
G MASS Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in London
✨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 ML projects, especially those that highlight your experience with model deployment and analytics tools. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to explain complex concepts clearly, as you'll need to communicate effectively with both technical and non-technical teams.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team.
We think you need these skills to ace Senior Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Senior Machine Learning Engineer. Highlight your experience with ML lifecycle tooling, Python applications, and any relevant projects that showcase your skills in a way that 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 this role and how your background in statistics and data science makes you a perfect fit. Don’t forget to mention your experience with tools like Kubernetes and Docker!
Showcase Your Projects: If you’ve worked on any relevant projects, make sure to include them in your application. Whether it’s a personal project or something from your previous job, showing us your hands-on experience with ML platforms and analytics tools can really set you apart.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, it shows us you’re keen to join our team!
How to prepare for a job interview at G MASS Consulting
✨Know Your ML Lifecycle
Make sure you can confidently discuss the full machine learning model lifecycle. Be prepared to share specific examples of how you've managed model deployment, monitoring, and alerting in past projects. This will show your depth of experience and understanding of the role.
✨Brush Up on Statistical Methods
Since the job requires a solid understanding of statistical methods, take some time to review key concepts like Generalised Linear Models (GLMs) and modern ML techniques. Being able to explain these clearly will impress your interviewers and demonstrate your expertise.
✨Showcase Your Coding Skills
Be ready to discuss your experience with Python applications, especially using libraries like pandas and scikit-learn. If possible, prepare to walk through a code sample or project that highlights your ability to build and deploy production-quality applications.
✨Communicate Effectively
This role involves collaborating with both technical and non-technical teams, so practice explaining complex concepts in simple terms. Think of examples where you've successfully communicated technical details to diverse audiences, as this will be crucial for your success in the position.
