Junior AI Researcher

EveryWatch is the only global online watch information platform, providing comprehensive and reliable watch data from brands, auction houses and marketplaces globally. The platform provides access to information and analysis not available anywhere else, enabling watch lovers and industry professionals to make educated decisions quickly and easily. It includes a meta-search for luxury watches currently available for sale at auction houses and marketplaces worldwide, a database of historical sales prices dating back to 1989, the ability to track watches coming to market; and powerful analysis tools unparalleled in the watch market. - EveryWatch is a Nace Capital Portfolio company and is now looking for a Junior AI Reseracher to join their team!

Responsibilities

• Design, Adapt and implement ML and classic algorithms from a POC to a working prototype

• Shape and perform experiments to answer business questions

• Design and develop model tests and statistical verification

• Implement data processing and training pipelines

• Extend existing ML / DL code and frameworks

• Log and document extensively POCs and experiments

• Keep abreast of developments in the field

Requirements

Requirements:

• Proven experience developing image/video processing and computer vision solutions is a

must

• Proven experience as a machine learning engineer/researcher or similar role

• Proficiency with common ML python frameworks (scikit-learn, scipy, matplotlib, TensorFlow /

Keras or PyTorch, etc.)

• Understanding of data structures, data modeling, and software architecture

• Ability to write clean and robust code

• Excellent communication and presentation skills (English)

• MSc/PhD in Computer Science / Engineering, Mathematics. BSc with an equivalent

experience will be considered as well

Advantages:

• Experience with deploying ML/AI systems in production is a plus

• Databases (SQL / Mongo) and basic networking / message passing knowledge is an

advantage

• Familiarity with common cloud platforms (GCP/AWS/Azure)

• Familiarity with containers (Docker and kubernetes)

• Experience with DVC, MLflow, MetaFlow, Databricks and other MLOps frameworks

• Experience with CI/CD tools (Jenkins, git pipes, Screwdriver, Spinnaker or others)