Senior ML Engineer, Marketing Personalization & Growth

DTU — Technical University of Denmark; København; Hybrid; DKK 900,000 - 1,300,000; Full time

Benefits offered by this job

Global impact

Autonomy in product teams

International company with 1,300+ Cols

Job summary

Too Good To Go is seeking a Senior Machine Learning Engineer to join the Marketing Personalisation team in Copenhagen. You will help define, build, and deploy AI features that personalize marketing and improve meal recommendations for millions of users.

You will work with data scientists, engineers, and product peers to create real value and measurable improvements in retention and engagement. The role emphasizes experimentation, end-to-end ML workflow, and production-ready solutions that scale

Qualifications

• Experience building production ML models for marketing personalization.
• Strong Python and ML library proficiency.
• Experience deploying to production and collaborating with data scientists and engineers.

Responsibilities

• Research, build, and design different ML models for marketing personalization.
• Run experiments, evaluate results, and improve models.
• End-to-end ownership from problem framing to production deployment.
• Collaborate with the team to improve the product and user experience.

Skills

Python

PyTorch

TensorFlow

Scikit-learn

Prophet

DeepAR

AWS

GCP

Azure

Metaflow

Airflow

Snowflake

dbt

MLOps

Production deployment

OpenSearch

Education

CS degree or related engineering field

Tools

Metaflow

GitHub

Jenkins

Docker

Airflow

OpenSearch

Redshift

Job description

Too Good To Go is seeking a Senior Machine Learning Engineer to join the Marketing Personalisation team in Copenhagen. You will help define, build, and deploy AI features that personalize marketing and improve meal recommendations for millions of users.

You will work with data scientists, engineers, and product peers to create real value and measurable improvements in retention and engagement. The role emphasizes experimentation, end-to-end ML workflow, and production-ready solutions that scale