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- Tasks: Design and deploy machine learning models to optimise supply chain efficiency and reduce waste.
- Company: Join Oddbox, a leader in sustainable eating and reducing food waste through innovative tech solutions.
- Benefits: Enjoy a hybrid work model, competitive salary, and the chance to make a real impact.
- Why this job: Be part of a mission-driven team that values innovation and sustainability while enhancing customer experiences.
- Qualifications: Experience in machine learning model development and cloud platforms is essential; strong problem-solving skills required.
- Other info: This is a fixed-term contract for 3 months with potential future opportunities.
The predicted salary is between 36000 - 60000 £ per year.
Location: Hybrid, at least one day per week in our office in Vauxhall, London.
Working Pattern: Full-time, fixed term contract for 3 months.
Salary: Competitive, based on experience.
This is a London based role, requiring time in our office most weeks. We are unable to accept applications from contractors who are not based in the UK.
Oddbox continues to revolutionise the fruit and veg subscription market with our commitment to reducing food waste and promoting sustainable eating. We’ve saved over 50 million kilograms of produce from going to waste, but we’re not stopping there. As we expand our tech-driven approach, we’re looking for a talented Machine Learning Engineer to join our innovative team.
About the Role
As a Machine Learning Engineer, you will rapidly design, build, and deploy machine learning forecasting and recommendation models that directly reduce waste and optimise supply chain efficiency through accurate prediction of customer behavior and preferences. You'll work closely with cross-functional teams to implement data-driven solutions that enhance customer experience and optimise our supply chain processes. This is a unique opportunity to contribute to a mission-driven company on a fixed-term basis, with the potential for future opportunities.
Key Responsibilities
- Develop cutting-edge machine learning models to enhance operational efficiency and improve the customer experience.
- Collaborate with data & software engineers, and product managers to integrate ML solutions into our tech stack.
- Analyse large datasets to extract meaningful insights and predictive analytics.
- Continuously evaluate and improve model performance through rigorous testing and validation.
- Stay updated with the latest industry trends to ensure our ML techniques remain at the forefront.
- Document processes, methodologies, and findings for internal knowledge sharing.
Qualifications and Skills
- Proven experience in developing and deploying machine learning models in a commercial setting.
- Experience with cloud-based ML platforms and tools (AWS, Azure, or Google Cloud).
- Strong problem-solving abilities and attention to detail.
- Excellent communication skills, capable of explaining complex technical concepts to non-technical stakeholders.
- Familiarity with data pipelines, ETL processes, and big data technologies.
Our interview process includes:
- A brief introductory call with our team (approximately 15 minutes).
- A take-home technical task with an asynchronous review.
- A combined technical live review and ways of working interview (approximately 1 hour).
Machine Learning Engineer (FTC) (London) employer: Oddbox
Contact Detail:
Oddbox Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (FTC) (London)
✨Tip Number 1
Familiarise yourself with the latest machine learning trends and tools, especially those related to cloud platforms like AWS, Azure, or Google Cloud. This knowledge will not only help you in interviews but also demonstrate your commitment to staying current in the field.
✨Tip Number 2
Prepare to discuss specific projects where you've developed and deployed machine learning models. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will showcase your problem-solving abilities.
✨Tip Number 3
Practice explaining complex technical concepts in simple terms. Since you'll be collaborating with non-technical stakeholders, being able to communicate effectively will set you apart from other candidates.
✨Tip Number 4
Engage with the community by participating in forums or attending meetups related to machine learning. Networking can provide valuable insights and may even lead to referrals, increasing your chances of landing the job with us.
We think you need these skills to ace Machine Learning Engineer (FTC) (London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly any projects where you've developed and deployed models. Emphasise your familiarity with cloud-based ML platforms like AWS, Azure, or Google Cloud.
Craft a Compelling Cover Letter: In your cover letter, express your passion for reducing food waste and promoting sustainable eating. Mention how your skills align with Oddbox's mission and the specific responsibilities of the Machine Learning Engineer role.
Showcase Problem-Solving Skills: Provide examples in your application that demonstrate your strong problem-solving abilities. Discuss specific challenges you've faced in previous roles and how you overcame them using machine learning techniques.
Prepare for Technical Assessment: Since the interview process includes a take-home technical task, brush up on your machine learning knowledge and be ready to showcase your skills. Familiarise yourself with common algorithms and be prepared to explain your thought process clearly.
How to prepare for a job interview at Oddbox
✨Understand the Company Mission
Before your interview, make sure you understand Oddbox's commitment to reducing food waste and promoting sustainable eating. Be prepared to discuss how your skills as a Machine Learning Engineer can contribute to this mission.
✨Showcase Your Technical Skills
Be ready to discuss your experience with developing and deploying machine learning models. Highlight specific projects where you've used cloud-based ML platforms like AWS, Azure, or Google Cloud, and be prepared to explain your approach to problem-solving.
✨Prepare for the Technical Task
Since there’s a take-home technical task involved, practice similar tasks beforehand. Focus on demonstrating your ability to analyse large datasets and extract meaningful insights, as this will be crucial for the role.
✨Communicate Clearly
During the interview, remember that you'll need to explain complex technical concepts to non-technical stakeholders. Practice simplifying your explanations and use relatable examples to ensure clarity in your communication.
