Senior Applied Machine Learning Engineer – Catalogue Intelligence

📋 Description

• You will be responsible for managing the structure, validation, and utilization of product data throughout the platform.

• Enhancing our classification and comprehension of products on a large scale.

• Elevating the overall quality of catalogue data and establishing what constitutes "good" data.

• Ensuring that product data facilitates effective searching, filtering, and discovery.

• Recognizing gaps in our catalogue and highlighting opportunities for expansion.

• Optimizing the performance of our catalogue across external channels.

• You will develop and refine the systems and decision-making processes that support this work, iterating based on real-world performance and data insights.

• Your work will encompass:

• • Structured data (catalogue attributes, GTINs, taxonomy)
• • Unstructured data (text and images)
• • Behavioral data (search, clicks, conversions)

⛳️ Requirements

• Proven experience in building and deploying production data or ML systems that have a measurable impact on business outcomes.

• Proficient in Python and SQL, with the ability to manage data pipelines from start to finish.

• You should be adept at applying contemporary methodologies such as LLMs, multimodal models, and information extraction techniques, transitioning them from experimentation to production with appropriate evaluation, monitoring, and cost management.

• Experience with complex, unstructured, or semi-structured data (such as text, images, and product data).

• Capability to design systems that make decisions rather than just predictions.

• Strong judgment in balancing accuracy, risk, and business impact.

• Experience with e-commerce or marketplace catalogues is advantageous, though not mandatory.

🏝️ Benefits

• Company Equity - In recognition of your contributions to our growth, we offer company equity, allowing you to own a part of the business we are collectively striving to build.

• 25 days of annual leave plus Bank Holidays.

• An additional day off for your Birthday.

• Employee Assistance Programme.

• Perks at Work benefit platform.

• Opportunities for career development and advancement.