Job Description

As a Machine Learning Engineer at Pollen, you will support us to improve the quality of our data and build AI models to solve liquidation pains, so our customers like L'Oréal and Unilever can avoid throwing away millions of tonnes of usable FMCG goods that otherwise could go to families in need of discounted goods.

If you care about building products with lasting impact - helping our business leaders and partners make sustainable decisions in reducing business waste, we look forward to working with you!

Primary Responsibilities
● Applies supervised and unsupervised learning techniques for solving pattern recognition problems (detection, classification, regression).
● Maintain and improve machine learning models in production and build new ones.
● Understands and interprets data to come up with optimal feature sets.
● Prepares datasets to train and validate models.
● Deploys the machine learning algorithms into our production environment.
● Documents and presents the work in a complete and consistent way.

Ideally, you’ll have:
● At least 2 years of experience in Machine Learning / Data Science / Data
Engineering.
● Proven Experience in Data Engineering and building ETL pipelines.
● Good knowledge and proven experience in supervised/unsupervised learning in
different applications: image recognition, classification, recommendation, etc.
● Proven experience in starting projects and work closely with stakeholders to
integrate your models into real world applications
● Proven experience in deploying and maintaining Machine Learning algorithms in
production.
● Solid programming skills in Python
● Good knowledge on building Data Warehouse/Lake from scratch
● Knowledge on databases (SQL and NoSQL).
● Experience in early stage startups or building things from scratch is highly
desirable