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- Tasks: Lead the design and build of cutting-edge machine learning systems and pipelines.
- Company: Join a specialist AI consultancy focused on impactful, high-stakes projects.
- Benefits: Flexible working with optional HQ visits, competitive salary, and growth opportunities.
- Why this job: Make a real-world impact by delivering safe, production-grade AI solutions.
- Qualifications: Strong Python skills and experience in deploying ML models in production.
- Other info: Fast-paced environment with opportunities for mentorship and leadership.
The predicted salary is between 43200 - 72000 ÂŁ per year.
2 days a week on UK client site, optional London HQ visits.
About the Company
We’re partnering with a specialist AI and data consultancy that designs and deploys bespoke machine learning systems across sectors such as national security, defence, critical infrastructure, and digital public services. Their focus is on delivering safe, production‑grade AI solutions that drive real‑world outcomes for complex, high‑stakes environments. This is a fast‑paced, technically elite environment, ideal for someone who thrives on solving operational challenges, building robust MLOps infrastructure, and leading the delivery of AI systems at scale.
Role
As a Senior Machine Learning Engineer, you’ll be part of cross‑functional delivery teams working on technically complex, high‑impact AI projects. You’ll play a central role in designing and building the ML architecture (from infrastructure and deployment to tooling and automation) to ensure that solutions are not only technically sound, but also scalable, maintainable, and secure. This is a hands‑on role with scope for team leadership, stakeholder engagement, and shaping best practices around modern MLOps. You’ll work alongside data scientists, engineers, designers, and product stakeholders often embedded within mission‑critical delivery environments.
Key Responsibilities
- Lead the design and build of production‑ready machine learning pipelines and systems
- Develop infrastructure and tooling to enable deployment, monitoring, and retraining of ML models
- Work across the full AI delivery lifecycle, from architecture and integration to performance optimisation
- Collaborate with customers and stakeholders to understand operational constraints and align on solution design
- Mentor junior engineers and shape internal technical standards for software quality, reliability, and reproducibility
- Support the continuous improvement of delivery practices, internal tooling, and knowledge sharing across teams
What We’re Looking For
- Strong software engineering skills, especially in Python.
- Experience building robust systems for ML applications
- Proven track record deploying machine learning models in production (using frameworks such as Scikit‑learn, TensorFlow, or PyTorch)
- Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling
- Hands‑on experience with Docker and Kubernetes in real‑world engineering workflows
- Solid grasp of ML fundamentals: supervised/unsupervised learning, statistical modelling, evaluation
- A pragmatic approach to engineering capable of balancing speed, risk, and delivery in complex environments
- Excellent communication and collaboration skills, especially in client‑facing settings
- Prior experience in a fast‑paced or start‑up environment is highly valued
If this role interests you and you would like to find out more (or find out about other roles), please apply here or contact us via (feel free to include a CV for review).
Location: London, England, United Kingdom
Senior Machine Learning Engineer in England employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in England
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the field. Building relationships can open doors that a CV just can’t.
✨Show Off Your Skills
Don’t just talk about your experience; showcase it! Create a portfolio of your projects, especially those involving machine learning pipelines or MLOps. This gives potential employers a taste of what you can do.
✨Ace the Interview
Prepare for technical interviews by brushing up on your Python skills and ML frameworks like TensorFlow or PyTorch. Practice explaining your thought process clearly, as communication is key in client-facing roles.
✨Apply Through Us!
If this role sounds like your cup of tea, don’t hesitate to apply through our website! We’re here to help you land that dream job, so let’s make it happen together.
We think you need these skills to ace Senior Machine Learning Engineer in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning and software engineering. Use keywords from the job description to show that you’re a perfect fit for the role.
Showcase Your Projects: Include specific examples of ML projects you've worked on, especially those involving deployment and MLOps. This will help us see your hands-on experience and problem-solving skills in action.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're excited about this role and how your background aligns with our needs. Be genuine and let your personality shine through!
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 don’t miss out on any important updates.
How to prepare for a job interview at Xcede
✨Know Your Tech Inside Out
Make sure you’re well-versed in the key technologies mentioned in the job description, like Python, Scikit-learn, TensorFlow, and cloud platforms. Brush up on your knowledge of MLOps practices and be ready to discuss how you've applied these in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex operational challenges in previous roles. Think about times when you built robust ML systems or optimised performance, and be ready to explain your thought process and the impact of your solutions.
✨Engage with Stakeholders
Since this role involves collaboration with clients and stakeholders, practice articulating how you would approach understanding their needs. Be prepared to discuss how you’ve successfully aligned technical solutions with operational constraints in past projects.
✨Demonstrate Leadership and Mentorship
If you have experience mentoring junior engineers or shaping best practices, make sure to highlight this during your interview. Share examples of how you’ve contributed to team development and improved internal standards, as this will show your potential for leadership in the role.