Senior ML Engineer: Build Production AI at Scale

Teampicnic; Amsterdam; Sur place; EUR 90 000 - 130 000; Plein temps

Avantages offerts par ce poste

Fresh lunch & snacks

Health insurance discount

Bike plan

Relocation support

Pension plan

Phone and laptop provided

25 holidays

Résumé du poste

Picnic is seeking a Machine Learning Engineer to design and deploy intelligent systems, productionize models, and monitor them in live environments. You will collaborate with stakeholders to ensure real-world impact using high-quality data.

You’ll join a role that blends consultancy, software engineering, and applied mathematics, working across projects like demand forecasting, fraud detection, and recommendations to improve our services and customer experience.

Qualifications

• Master’s degree or higher in AI, CS, Math, or related field.
• 5+ years of experience in data science or applied ML.
• Excellent communication with business stakeholders.
• Experience designing, deploying, and maintaining production ML systems.
• Strong Python and SQL skills.
• Ability to define long-term ML architecture within your domain.
• Experience with Docker, Kubernetes, and CI is a plus.

Responsabilités

• Identify and execute improvement possibilities with ML engineers and analysts.
• Collaborate from inception to production, and for continuous improvement.
• Develop tools for our cloud-based ML platform.
• Work on projects such as demand forecasting, fraud detection, recommendations, search/ranking, delivery timing, and vision to ensure quality and efficiency.

Connaissances

Python

SQL

Communication

Data science

ProductionML

Formation

Master’s degree or higher in AI/CS/Math

Outils

Docker

Kubernetes

CI

Description du poste

Picnic is seeking a Machine Learning Engineer to design and deploy intelligent systems, productionize models, and monitor them in live environments. You will collaborate with stakeholders to ensure real-world impact using high-quality data.

You’ll join a role that blends consultancy, software engineering, and applied mathematics, working across projects like demand forecasting, fraud detection, and recommendations to improve our services and customer experience.