Full-Time Senior Research Scientist

Develop and apply machine learning innovations to business problems with minimal technical supervision.

Code high-quality architecture around ML models, creating robust, readable, and reusable code.

Assess your own and others’ results to understand their applicability in the real world.

Understand stakeholders’ requirements and communicate results and conclusions accurately, clearly, and winsomely.

Perform feasibility studies and analyze data to determine the most appropriate solution.

Maintain and develop data and software with high-quality standards and minimal defects.

Collaborate with technical colleagues on the integration and deployment of ML solutions.

Build strong relationships within the team and with stakeholders across the company.

Bachelor's degree in computer science or an equivalent numerate discipline.

Demonstrated senior-level experience in Machine Learning and Deep Learning using Pytorch.

Experience performing EDA with large datasets and writing production-grade code.

High-quality coding and an understanding of SOLID principles.

Analytical mindset, problem-solving, and logical thinking capabilities.

High level of interpersonal and presentation skills in English across cultures.

Keen to work as part of a diverse team of international colleagues and in a global inclusive culture.

Python, Pytorch, Git, pandas, sklearn, huggingface

A minimum of 5 years’ experience with evidence in a related ML field.

Good to Have: Master’s degree and/or specialization courses in ML/DL/NLP. Experience in MLOPs. Understanding and practice of Generative AI (prompt engineering, RAG). A practical grasp of databases (SQL, ElasticSearch) and Databricks. Experience in retail, consumer, ecommerce, business, FMCG domain.

Home office - SPAIN ONLY

Enjoy a warm, flexible, and rewarding work environment. Recharge and revitalize with help of wellness plans made for you and your family. Plan your future with financial wellness tools. Stay relevant and upskill yourself with career development opportunities.

• Flexible working environment
• Volunteer time off
• LinkedIn Learning
• Employee-Assistance-Program (EAP)

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