Senior Applied Machine Learning Engineer – Catalogue Intelligence

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• You will take charge of the organization, validation, and utilization of product data throughout the platform.

• Enhance the classification and understanding of products on a large scale.

• Elevate the overall quality of catalogue data while establishing standards for what constitutes "good".

• Ensure that product data facilitates effective search, filtering, and discovery processes.

• Identify deficiencies in our catalogue and highlight opportunities for expansion.

• Optimize the performance of our catalogue across external channels.

• You will develop and refine the systems and decision-making processes that support these objectives, iterating based on actual performance and data insights.

• Your work will span:

• - 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 machine learning systems that deliver measurable business results.

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

• You should be adept at employing 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 dealing with disorganized, unstructured, or semi-structured data (e.g., text, images, product information).

• Ability to design systems that make decisions rather than merely predictions.

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

• Familiarity with ecommerce or marketplace catalogues is beneficial but not mandatory.

🏝️ Benefits

• Company Equity - In appreciation for your contributions to our growth, we offer you company equity, enabling you to own a share 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.