Rosetta.ai helps fashion e-commerce uncover consumer's shopping preferences and provide personalized shopping experiences to consumers. We're making e-commerce merchants have enterprise-level AI backup on day 1.

We are seeking Machine Learning Engineers to join our engineering team. The ideal person will have industry experience working on a range of classification and optimization problems, e.g. click-through rate prediction, recommendation systems, or search ranking. The position will involve taking these skills and applying them to some of the most exciting and massive shopping data and prediction problems that exist on the web. You will bring the ability to own the whole ML life cycle, define projects, and drive excellence across teams.

Responsibilities:

• Develop and maintain the core Rosetta.ai recommender system and analytical reports.
• Lead machine learning model deployment and production execution.
• Collaborate with product owners and business development teams to ensure the quality and stability of data-driven products.
• Research and implement new recommender system models.
• Evaluate the effectiveness of the deployed ML model.
• Maintain all workflow documents of data-driven products up to date.

Contact:

• Email to [email protected]
• Or, send us on CakeResume

Remarks:

Rosetta.ai is an Equal Employment Opportunity employer. Rosetta.ai conducts all employment-related activities without regard to race, religion, color, national origin, age, sex, marital status, sexual orientation, disability, citizenship status, genetics, or any other characteristic protected by law.

[Minimum Qualifications]

Background & Skills:

• Experience in one or more of the following areas: machine learning, recommendation systems, computer vision, or natural language processing. 
• Expert knowledge developing production-level ML products. 
• Minimum 2 years of relevant and hands-on experience in: 
  • Numpy, Pandas, Scikit-Learn, PyTorch, SQL, Jupyter Notebook 
  • AWS, S3, EC2, Beanstalk 
• Experience of demonstrating technical leadership working with teams, owning projects, defining and setting technical direction for projects.

Working Style:

• Excellent communication and collaborative skills.
  
• Strong problem solving and conceptual thinking skills. 
• Flexibility and comfort working in a dynamic, team environment with a possible remote organization with minimal documentation and process.

[Preferred Qualifications] (Optionally, the more, the better)

Background & Skills:

• MS degree in Computer Science or related quantitative field with 2-3+ years of machine learning related work or research, or Ph.D. degree in Computer Science or related quantitative field.

Experience:

• Experience with computer vision, or natural language processing. 
• Experience with filesystems, server architectures, and distributed systems.
• Experience with Elasticsearch.