Machine Learning Engineer (FTC) (London)

Location: Hybrid, at least one day per week in our office in Vauxhall, London.

WorkingPattern: 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).

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