Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Support the development of AI solutions and transition machine learning models into production.
- Company: Join Rightmove's innovative Data, Analytics & AI team in London.
- Benefits: Enjoy competitive pay, private medical insurance, and 27 days holiday plus volunteering days.
- Other info: Hybrid working model with opportunities for personal and professional growth.
- Why this job: Kickstart your career in machine learning with hands-on experience and mentorship from experts.
- Qualifications: Solid understanding of machine learning concepts and some experience with Python and SQL.
The predicted salary is between 30000 - 40000 £ per year.
Location: London. Reporting to: Head of AI.
The Role
We’re looking for an Associate Machine Learning Engineer to join Rightmove’s growing Data, Analytics & AI team. This is an excellent opportunity for someone at an early stage in their career to contribute to the development of AI-powered solutions while building strong foundations in machine learning engineering and MLOps. You’ll work closely with experienced engineers and data scientists to help bring machine learning models into production, supporting the development of reliable, scalable, and impactful AI features. This role would suit someone who is keen to learn, enjoys solving practical problems, and wants to develop their skills within a collaborative, product‑focused environment.
What You’ll Be Doing
- Supporting the transition of machine learning models from experimentation into production
- Assisting in the development and maintenance of ML pipelines (training, deployment, and monitoring)
- Contributing to internal tools or prototypes to help test and validate AI concepts
- Working with data scientists and engineers to improve model performance and reliability
- Supporting the monitoring of models in production, identifying issues such as performance degradation or data drift
- Writing clear, maintainable code to support data processing and model deployment
- Collaborating with product, engineering, and data teams to support delivery of AI features
- Learning and applying best practices in MLOps, including version control, testing, and reproducibility
We’re Looking For Someone Who
- Has a solid understanding of core machine learning concepts and the ML lifecycle
- Has some experience with Python and SQL (through academic work, projects, or early commercial experience)
- Is familiar with at least one ML framework (e.g. PyTorch, TensorFlow, or Scikit‑learn)
- Has some exposure to cloud platforms (e.g. GCP, AWS, or Azure), or a willingness to learn
- Is comfortable using Git and basic development workflows
- Is curious, proactive, and keen to develop new skills
- Communicates clearly and enjoys working as part of a team
Nice to have
- A degree in Computer Science, Engineering, Data Science, or a related STEM subject
- Internship, placement year, or project experience involving machine learning or data engineering
- Exposure to data pipelines, APIs, or backend development concepts
- Familiarity with containerisation (e.g. Docker) or workflow tools (e.g. Airflow)
- An interest in modern AI approaches such as LLMs or applied AI use cases
- Basic understanding of Software Engineering principles
- Exposure to API development
What We Offer
- Cash plan for dental, optical and physio treatments
- Private Medical Insurance, Pension and Life Insurance, Employee Assistance Plan
- 27 days holiday plus two (paid) volunteering days a year to give back, and holiday buy schemes
- Contributory stakeholder pension
- Life assurance at 4x your basic salary to a spouse, family member or other nominated person in your life
- Competitive compensation package
- Paid leave for maternity, paternity, adoption & fertility
- Travel Loans, Bike to Work scheme, Rental Deposit Loan
- Charitable contributions through Payroll Giving and donation matching
- Access deals and discounts on things like travel, electronics, fashion, gym memberships, cinema discounts and more
- We offer hybrid working with a minimum of 2 days in the office. For our roles, such as Field or Home‑based positions, different working arrangements apply – full details will be shared during the recruitment process
Equal Opportunity Statement
As an Equal Opportunity Employer, Rightmove will never discriminate based on age, disability, sex, race, religion or belief, gender reassignment, marriage / civil partnership, pregnancy/maternity or sexual orientation. We believe that a diverse and inclusive workforce leads to better innovation, productivity, and overall success, and we are committed to creating a welcoming and inclusive environment for all employees, regardless of their background or identity, to develop and promote a diverse culture that reflects the communities we serve.
Associate Machine Learning Engineer in London employer: Rightmove
Contact Detail:
Rightmove Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Associate Machine Learning Engineer in London
✨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 projects, especially those involving machine learning. 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 common machine learning concepts and coding challenges. Practice explaining your thought process clearly, as communication is key in collaborative environments like Rightmove.
✨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, it shows you’re genuinely interested in joining our team at Rightmove.
We think you need these skills to ace Associate Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Associate Machine Learning Engineer role. Highlight your relevant skills in Python, SQL, and any ML frameworks you've used. We want to see how your experience aligns with what we're looking for!
Show Your Passion for Learning: In your application, let us know about your eagerness to learn and grow in the field of machine learning. Mention any projects or coursework that demonstrate your curiosity and proactive approach. We love candidates who are keen to develop their skills!
Be Clear and Concise: When writing your application, keep it clear and to the point. Use straightforward language to explain your experiences and skills. We appreciate well-structured applications that make it easy for us to see your potential.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it helps us keep everything organised on our end.
How to prepare for a job interview at Rightmove
✨Know Your Machine Learning Basics
Make sure you brush up on core machine learning concepts and the ML lifecycle. Be ready to discuss how you've applied these in your projects or studies, as this will show your understanding and enthusiasm for the role.
✨Showcase Your Coding Skills
Since you'll be writing clear, maintainable code, it's crucial to demonstrate your proficiency in Python and SQL. Prepare to talk about any relevant projects where you've used these languages, and maybe even bring along some code samples to discuss.
✨Familiarise Yourself with MLOps Practices
Understanding MLOps is key for this role. Brush up on best practices like version control, testing, and reproducibility. You might want to mention any experience you have with tools like Git or cloud platforms, as this will highlight your readiness to dive into the work.
✨Be Curious and Collaborative
This role is all about teamwork and problem-solving. Show your curiosity by asking insightful questions about the team’s current projects or challenges. Highlight any past experiences where you worked collaboratively, as this will resonate well with their product-focused environment.