At a Glance
- Tasks: Lead and innovate in machine learning projects, shaping the future of AI solutions.
- Company: Dynamic AI consultancy partnering with top global brands.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Join a collaborative team focused on driving machine learning innovation.
- Why this job: Make a real impact in the AI space while working with cutting-edge technologies.
- Qualifications: Expertise in Python, ML deployment, and cloud platforms required.
The predicted salary is between 110000 - 130000 € per year.
Our client partners with some of the world’s most recognisable brands to deliver innovative, data-driven solutions that transform customer experience, strategy, and performance. From global enterprises to digital-first disruptors, they help businesses harness the power of advanced analytics, machine learning, and AI to stay competitive in a rapidly changing market. If you’re looking for an opportunity to shape the future of applied AI across exciting industry sectors, this is your chance.
ROLES
- Senior ML Engineers (Up to £110K)
- Build & deploy production-grade ML systems, tools, and infrastructure at scale
- Design scalable, reusable solutions and lead technical architecture & delivery standards
- Partner with engineers, data scientists, and stakeholders to solve key problems and translate ML into real-world impact
- Lead Machine Learning Engineers (Up to £130K)
- Set technical direction, guide priorities, and make key architectural decisions on complex ML projects
- Design & deliver scalable ML systems, owning roadmaps and execution across ambiguous, high-risk workstreams
- Build and elevate teams — hiring, mentoring, and driving shared engineering standards
- Act as a trusted advisor to stakeholders, shaping strategy and adopting new technologies to stay ahead
What You’ll Bring
- Go-to technical specialist with deep expertise and broad problem-solving ability
- Strong Python background with hands‑on ML deployment (TensorFlow, PyTorch, Scikit-learn)
- Cloud expert (AWS/Azure/GCP) with experience building and leading full‑stack solutions
- Skilled in containerisation and orchestration (Docker, Kubernetes)
- Proven leader — coaching teams, owning delivery, and partnering effectively with stakeholders
Apply now and become a key player driving machine learning innovation.
Senior Machine Learning Engineer employer: Loop Recruitment
As a Senior Machine Learning Engineer at our AI consultancy in Central London, you'll join a dynamic team that thrives on innovation and collaboration. We offer a hybrid work model, competitive salaries, and a culture that prioritises professional growth through mentorship and technical leadership opportunities. With access to cutting-edge technologies and the chance to work with renowned global brands, this role is perfect for those looking to make a significant impact in the field of applied AI.
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 your connections in the AI and machine learning space. Attend meetups, webinars, or even local tech events. 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 projects, especially those involving Python, TensorFlow, or any cloud platforms. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with MLOps, containerisation, and how you've led teams or projects. Practice common interview questions to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you. Tailor your application to highlight your leadership and technical skills, and let us help you land that dream role in machine learning.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your expertise in Python, cloud platforms, and machine learning frameworks to catch our eye!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about machine learning and how you can contribute to our innovative projects. Share specific examples of your past work that align with the role.
Showcase Your Projects:If you've worked on any relevant ML projects, make sure to include them in your application. We love seeing real-world applications of your skills, especially if they demonstrate your leadership and problem-solving abilities.
Apply Through Our Website:For the best chance of getting noticed, apply directly through our website. It helps us keep track of your application and ensures it reaches the right people quickly!
How to prepare for a job interview at Loop Recruitment
✨Know Your Tech Inside Out
Make sure you’re well-versed in the key technologies mentioned in the job description, like Python, TensorFlow, and cloud platforms. Brush up on your knowledge of MLOps and container orchestration with Docker and Kubernetes, as these will likely come up during technical discussions.
✨Showcase Your Leadership Skills
As a Senior Machine Learning Engineer, you'll need to demonstrate your ability to lead teams and projects. Prepare examples of how you've successfully guided teams, made architectural decisions, or mentored others in previous roles. This will show that you can take ownership and drive results.
✨Prepare for Real-World Scenarios
Expect to discuss how you’ve translated machine learning concepts into practical solutions. Think of specific projects where you’ve built production-grade ML systems or solved complex problems. Be ready to explain your thought process and the impact of your work on stakeholders.
✨Communicate Clearly and Confidently
Strong stakeholder communication is crucial for this role. Practice articulating your ideas clearly and concisely, especially when discussing technical topics. Use layman's terms when necessary to ensure everyone understands your points, showcasing your ability to bridge the gap between tech and business.
