Description:

Constructor.io is seeking a Machine Learning Engineer for the Attribute Enrichment team, which is responsible for implementing algorithms and training ML models to enhance product attributes.
The role involves building and deploying robust ML systems for attribute enrichment using state-of-the-art ML techniques.
Collaboration with both technical and non-technical business partners is essential to develop analytical dashboards that demonstrate the impact of Attribute Enrichment algorithms.
The engineer will work on improving business KPIs by validating hypotheses with new ML approaches and techniques.
The position is fully remote, allowing flexibility in work location.

Requirements:

Candidates must have 2+ years of professional experience in applied machine learning.
Proficiency in Python, SQL, and the big data stack is required for end-to-end ML product development.
A comprehensive knowledge of classical machine learning, including ranking and classification, is necessary.
Experience with deep learning, including neural networks and representation learning, is expected.
Skills in designing, conducting, and analyzing A/B tests are required.
Strong knowledge of data structures, algorithms, and their trade-offs is essential.
A proven track record of software architecture and design skills is necessary.
Experience with a public cloud platform such as AWS, Azure, or GCP is required.
Excellent communication skills to deliver and communicate business value are essential.

The position offers a fully remote work environment, allowing employees to choose their living location.
A work-from-home stipend is provided to help set up a home office.
New employees will receive Apple laptops to facilitate their work.
There is a training and development budget for every employee, refreshed annually.
Parental leave is available for qualified employees.
Employees will have the opportunity to work with intelligent colleagues who will support their growth and enable them to make a meaningful impact.
The compensation range for this position is between a base salary of 90-110k USD, plus stock options and stipends.