At a Glance
- Tasks: Build and deploy impactful AI solutions for diverse clients using machine learning.
- Company: Join a forward-thinking company focused on innovative AI technology.
- Benefits: Enjoy unlimited annual leave, private healthcare, and flexible working options.
- Other info: Dynamic work environment with a focus on diversity and inclusion.
- Why this job: Make a real-world impact with cutting-edge machine learning technologies.
- Qualifications: Experience with ML frameworks, strong Python skills, and cloud platform knowledge.
The predicted salary is between 60000 - 80000 £ per year.
About the role
Join us as a Machine Learning Engineer to deliver bespoke, impactful AI solutions for our diverse clients. You will be instrumental in bringing machine learning out of the lab and into the real world, contributing to scalable software architecture and defining best practices. Working with clients and cross‑functional teams, you'll ensure technical feasibility and timely delivery of high‑quality, production‑grade ML systems.
What you'll be doing:
- Building and deploying production‑grade ML software, tools, and infrastructure.
- Creating reusable, scalable solutions that accelerate the delivery of ML systems.
- Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges.
- Leading technical scoping and architectural decisions to ensure project feasibility and impact.
- Defining and implementing Faculty’s standards for deploying machine learning at scale.
- Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders.
Who we're looking for:
- You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit‑learn, TensorFlow, or PyTorch.
- You possess strong Python skills and solid experience in software engineering best practices.
- You bring hands‑on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security.
- You have worked with container and orchestration tools such as Docker & Kubernetes to build and manage applications at scale.
- You are comfortable with core ML concepts, including probability, statistics, and common learning techniques.
- You're an excellent communicator, able to guide technical teams and confidently advise non‑technical stakeholders.
- You thrive in a fast‑paced environment and enjoy the autonomy to own scope, solve and deliver solutions.
Eligibility for UK Developed Vetting (DV) and willingness to work on site with clients may be required.
Benefits:
- Unlimited Annual Leave Policy
- Private healthcare and dental
- Enhanced parental leave
- Family‑Friendly Flexibility & Flexible working
- Sanctus Coaching
- Hybrid Working
We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Machine Learning Engineer in London employer: jobr.pro
Join a forward-thinking company as a Machine Learning Engineer, where you'll have the opportunity to create impactful AI solutions in a collaborative and innovative environment. With benefits like unlimited annual leave, private healthcare, and a strong emphasis on family-friendly flexibility, we prioritise employee well-being and growth. Our hybrid working model and commitment to diversity make us an excellent employer for those seeking meaningful and rewarding careers in the heart of the tech industry.
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We think this is how you could land Machine Learning Engineer in London
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We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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✨Get Comfortable with Python and R
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
