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- Tasks: Design and build AI prototypes while collaborating with a dynamic team.
- Company: Join Olive Jar Digital, a forward-thinking company at the forefront of AI innovation.
- Benefits: Enjoy 25 days annual leave, health insurance, and an electric car scheme.
- Why this job: Make a real impact in AI/ML and enhance your skills in a supportive environment.
- Qualifications: Experience in ML engineering, strong coding skills, and a collaborative mindset.
- Other info: Remote work opportunity with excellent career growth and learning potential.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Olive Jar Digital is seeking a Machine Learning Engineer to help design, build, and refine AI prototypes across multiple Discovery and Alpha initiatives. You will work at the intersection of engineering and data scienceâtransforming experimental models into highâquality, scalable prototypes, shaping technical architecture, and ensuring robust deployment, testing, and documentation. This role is ideal for someone who enjoys handsâon technical problemâsolving, rapid iteration, and collaborating closely with data scientists, engineers, product managers, and researchers.
Responsibilities:
- Build, refine, and optimize AI/ML prototypes, ensuring they meet quality, security, and performance standards.
- Develop and maintain technical design documentation, including architecture, model pipelines, and integration patterns.
- Implement automated deployment pipelines, CI/CD flows, unit/regression testing, and monitoring/telemetry for prototypes.
- Deploy models into development and test environments and support iterative updates based on feedback.
- Collaborate with data scientists on model integration, feature engineering, and evaluation frameworks.
- Ensure codebases follow best practices in engineering, documentation, security, and accessibility. Support playback sessions, technical reviews, and knowledgeâtransfer activities.
About You:
- Strong experience as an ML Engineer or similar role within AI/ML product development.
- Proficiency in building ML pipelines, APIs, cloudâbased deployments, and automated testing.
- Solid software engineering skills (e.g., Python, version control, CI/CD, cloud platforms).
- Ability to work collaboratively with data scientists, engineers, and product teams.
- Comfortable producing clear, structured technical documentation.
- Experience with LLMs, vector databases, retrievalâaugmented generation, or intelligent search.
- Familiarity with MLOps tooling, containerisation, and cloudânative environments.
- Exposure to rapid prototyping in Discovery/Alpha phases.
Benefits:
- 25 Days Annual Leave per annum (plus 8 Bank Holidays as standard)
- Health Insurance
- Pension Scheme
- Annual Bonus Scheme
- Annual Salary Review
- Electric Car Scheme
Machine Learning Engineer in London employer: Olive Jar Digital
Contact Detail:
Olive Jar Digital Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Machine Learning Engineer in London
â¨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with other Machine Learning Engineers. You never know who might have the inside scoop on job openings or can refer you directly.
â¨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI prototypes and ML projects. This is your chance to demonstrate your hands-on problem-solving abilities and technical prowess to potential employers.
â¨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining your projects and how you collaborated with teams. Remember, they want to see how you fit into their culture as much as your technical skills!
â¨Tip Number 4
Donât forget to apply through our website! Weâve got loads of opportunities waiting for talented individuals like you. Plus, itâs a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application đŤĄ
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with ML pipelines, cloud deployments, and any relevant projects that showcase your skills in AI/ML product development.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're the perfect fit for this role. Share your passion for hands-on problem-solving and collaboration, and mention specific experiences that align with our responsibilities.
Showcase Your Technical Skills: Donât forget to highlight your technical skills! Mention your proficiency in Python, CI/CD, and any experience with MLOps tooling or containerisation. We want to see how you can contribute to our projects.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. Itâs the best way for us to receive your application and get to know you better!
How to prepare for a job interview at Olive Jar Digital
â¨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and techniques. Be ready to discuss your experience with building ML pipelines, APIs, and cloud-based deployments. Theyâll want to see that you can talk the talk and walk the walk!
â¨Show Off Your Collaboration Skills
Since this role involves working closely with data scientists, engineers, and product managers, be prepared to share examples of how you've successfully collaborated in the past. Highlight any projects where teamwork made a difference in achieving results.
â¨Prepare for Technical Questions
Expect some technical questions or even a coding challenge during the interview. Practice common algorithms and data structures, and be ready to explain your thought process. This is your chance to showcase your problem-solving skills!
â¨Documentation is Key
Theyâre looking for someone who can produce clear, structured technical documentation. Bring examples of your previous documentation work or be ready to discuss how you approach documenting your projects. This will show that you understand the importance of good documentation in engineering.
