Applied Scientist (AI)

Location: London, United Kingdom

Company

hirify.global is an online fashion retailer serving customers around the world through a technology-driven ecommerce platform.

What you will do

• Design, develop, deploy, and monitor machine learning models and data-driven solutions in production.
• Apply machine learning, statistical, quantitative, and optimisation techniques to complex business problems.
• Partner with data engineers, ML engineers, analysts, product managers, and business stakeholders to build scalable ML systems.
• Design experiments and evaluation frameworks to measure model performance, business impact, and customer outcomes.
• Explore and prototype approaches from industry and academia, contributing to technical direction and applied research.
• Help establish best practices through knowledge sharing, code reviews, and collaboration.

Requirements

• Experience developing and deploying machine learning models in production and taking ML products from ideation through deployment.
• Proficiency in Python and modern machine learning frameworks such as PyTorch or TensorFlow.
• Experience with large datasets, distributed data processing systems, and cloud-native ML platforms or MLOps practices.
• Strong software engineering practices, including testing, version control, and maintainable code.
• Ability to design and evaluate models using technical, business, and customer impact measures.
• Ability to communicate technical concepts to technical and non-technical audiences.

Nice to have

• Publications, open-source contributions, or evidence of staying current with machine learning and AI developments.
• Experience in fast-paced, product-driven environments.
• Experience translating research, experimentation, and analytical insights into production-ready solutions.

Culture & Benefits

• Inclusive, collaborative culture focused on authenticity, innovation, evidence-based decisions, and customer outcomes.
• Employee discount and sample sales.
• 25 days of annual leave plus an additional celebration day.
• Private medical care, pension contributions, and a discretionary bonus scheme.
• Personalised learning opportunities, summer hours, and access to office facilities including a gym and subsidised café.