At a Glance
- Tasks: Design and optimise machine learning models for real-world business challenges.
- Company: Join a dynamic team at a leading tech company focused on innovation.
- Benefits: Competitive salary, bonuses, discounts, and flexible benefits.
- Other info: Opportunities for personal growth and access to online learning resources.
- Why this job: Make an impact with cutting-edge ML solutions in a collaborative environment.
- Qualifications: Experience in machine learning and deep learning with strong teamwork skills.
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) 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 in your career. Our inclusive work culture fosters creativity and supports your professional journey, making it an excellent place for those looking to make a meaningful impact in the field of machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer (Recommenders)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow Machine Learning enthusiasts. 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 will give potential employers a taste of what you can do and set 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. We want to see how you think and approach real-world problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Machine Learning Engineer (Recommenders)
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. We love seeing enthusiasm and a bit of personality, so let us know what excites you about this role.
Showcase Collaboration Skills:Since you'll be working closely with data scientists and engineers, highlight any past experiences where you collaborated on projects. We value teamwork, so share examples that demonstrate your ability to communicate and work effectively across disciplines.
Apply Through Our Website:We encourage you to apply directly through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. 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 about specific projects where you collaborated effectively and how you contributed to the team's success.
✨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 version control or CI/CD practices, and how they helped streamline your projects.
✨Stay Current with Industry Trends
Research the latest advancements in machine learning and deep learning. Bring insights from recent studies or trends to the interview, showing your passion for continuous learning and how you can contribute fresh ideas to the team.
