At a Glance
- Tasks: Design and optimise machine learning models for real-world business challenges.
- Company: Join a dynamic team at the forefront of machine learning innovation.
- Benefits: Competitive salary, bonuses, discounts, and flexible benefits.
- Other info: Great opportunities for personal and professional growth in a thriving workplace.
- Why this job: Make a real impact with cutting-edge technology in a supportive environment.
- Qualifications: Experience in machine learning and a collaborative mindset are essential.
The predicted salary is between 50000 - 70000 £ per year.
We are seeking a Machine Learning Engineer with a strong foundation in Machine Learning/Deep Learning to join a cross‑functional team. You’ll work closely with data scientists and engineers to deliver impactful machine learning solutions across a wide range of data‑rich challenges. In this role, you’ll contribute to developing and deploying advanced algorithms that influence key areas like pricing strategies and personalised customer targeting, all at enterprise scale.
Key Responsibilities
- Collaborate with cross‑functional teams to design, implement, and optimise machine learning models for real‑world business use cases, with a focus on recommender systems.
- Deploy and maintain both batch and real‑time machine learning systems at scale.
- Work alongside data scientists to translate experimental models into robust production‑ready solutions.
- Continuously improve model accuracy, system efficiency, and platform capabilities.
- Contribute to defining team best practices and engineering standards in machine learning development.
- Stay up to date with the latest industry research and bring new insights to the wider ML community within the business.
Qualifications
- Hands‑on professional experience in developing and deploying machine learning solutions, with a focus on deep learning.
- Experience working with modern ML frameworks and familiarity with end‑to‑end deployment workflows.
- Proficiency in training models using GPUs, and a strong interest in distributed computing and scalable systems.
- Familiarity with software development practices including version control, CI/CD, containerisation, and monitoring, especially within ML Ops workflows.
- A collaborative mindset with strong communication skills and the ability to work effectively across multidisciplinary teams.
- Motivated self‑starter with a desire to learn, share knowledge, and grow in a fast‑paced environment.
Benefits
- Competitive salary and performance‑based bonus scheme
- Generous employee discount and exclusive product access
- Structured personal and professional development opportunities
- Paid annual leave plus an additional day for special personal milestones
- Flexible benefits allowance and private medical care options
- Access to a variety of online learning resources and employee‑led communities
- A supportive, inclusive, and dynamic workplace where innovation thrives
Machine Learning Engineer (Recommenders) in London employer: 慨正橡扯
As a Machine Learning Engineer at our company, you'll be part of a vibrant and innovative team that values collaboration and continuous learning. We offer competitive salaries, performance-based bonuses, and generous employee discounts, alongside structured development opportunities to help you grow your career in a supportive and inclusive environment. Located in a dynamic setting, our workplace fosters creativity and encourages you to stay at the forefront of machine learning advancements.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer (Recommenders) 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 machine learning projects, especially those related to recommender systems. 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 problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications come directly from passionate candidates. Plus, it shows you’re genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Machine Learning Engineer (Recommenders) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in machine learning and deep learning. 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 passionate about machine learning and how you can contribute to our team. Keep it conversational but professional, and let your personality come through.
Showcase Your Collaboration Skills:Since we work in cross-functional teams, it’s important to highlight your teamwork experience. Share examples of how you’ve successfully collaborated with data scientists or engineers in the past to deliver impactful solutions.
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’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at 慨正橡扯
✨Know Your Algorithms
Brush up on your knowledge of machine learning algorithms, especially those related to recommender systems. Be ready to discuss how you’ve implemented these in past projects and the impact they had on business outcomes.
✨Showcase Your Collaboration Skills
Since this role involves working closely with data scientists and engineers, prepare examples that highlight your teamwork experience. Think of specific instances where you successfully collaborated on a project and how it led to better results.
✨Demonstrate Your Technical Proficiency
Be prepared to talk about your hands-on experience with modern ML frameworks and deployment workflows. Discuss any relevant tools you've used, like GPUs for training models, and how you ensure your solutions are production-ready.
✨Stay Current with Industry Trends
Research the latest advancements in machine learning and deep learning. Bring insights or recent findings to the interview to show your passion for the field and your commitment to continuous learning.
