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- Tasks: Design and build production-ready machine learning systems in a fast-paced environment.
- Company: Join a leading AI consultancy focused on impactful, bespoke solutions.
- Benefits: Flexible working, competitive salary, and opportunities for professional growth.
- Why this job: Make a real-world impact with cutting-edge AI technology and lead innovative projects.
- Qualifications: Strong Python skills and experience with ML frameworks like TensorFlow or PyTorch.
- Other info: Collaborative team culture with mentorship opportunities and career advancement.
The predicted salary is between 43200 - 72000 £ per year.
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.
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
- 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 niall.wharton@Xcede.com (feel free to include a CV for review).
Senior Machine Learning Engineer employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals 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 machine learning projects, especially those that highlight your experience with Python, cloud infrastructure, and MLOps. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your past projects, how you tackled challenges, and your approach to collaboration. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are eager to make an impact in the AI space.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning and software engineering. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or technologies you've worked with!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about this role and how your background makes you a perfect fit. We love seeing genuine enthusiasm for AI and data consultancy.
Showcase Your Technical Skills: Be specific about your technical expertise, especially in Python, cloud infrastructure, and MLOps tools like Docker and Kubernetes. We’re looking for solid examples of how you’ve applied these skills in real-world scenarios.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team!
How to prepare for a job interview at Xcede
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and ML frameworks like TensorFlow or PyTorch. Brush up on your experience with cloud infrastructure and containerisation tools like Docker and Kubernetes, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex operational challenges in previous roles. Think about how you designed and built production-ready ML systems 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’ve successfully engaged with them in the past. Be ready to discuss how you’ve aligned technical solutions with operational constraints and how you’ve communicated complex ideas clearly.
✨Demonstrate Leadership Potential
Even if you’re not applying for a managerial position, highlight any mentoring or leadership experiences you have. Discuss how you’ve shaped best practices or contributed to team standards, as this shows you’re ready to take on more responsibility in a fast-paced environment.
