Total 2 quality assurance engineer job vacancies in singapore mto aml

We are seeking a dynamic Software Engineer (Python) to join our growing global team, Recommendations domain to work on exciting projects like implementation of our own machine learning framework, integrating a feature store for supporting real-time data science requirements and the creation of complex data ingestion pipelines to support this!

Join us in creating an engaging and personalized shopping experience for our users. Every feature and improvement you develop will enhance customer choice and app performance, making it easier for users to find and enjoy the products they love. Your work will have a lasting impact on customer satisfaction and loyalty across diverse markets.

Responsibilities

• Working closely with Data Scientists and Product Managers to run experiments on new recommendation features.
• Deploying low latency databases and datastores to support operational requirements of the recommender models.
• Working with senior engineers to maintain our API Gateway.
• Deploying and maintaining ML models on our deployment framework that power recommendations on all pages of the application.
• Enabling and actively managing observability tools on all touch points within our systems.

We are seeking a dynamic Data Engineer (Python) to join our growing global team, Recommendations domain to work on exciting projects like implementation of our own machine learning framework, integrating a feature store for supporting real-time data science requirements and the creation of complex data ingestion pipelines to support this!

Join us in creating an engaging and personalized shopping experience for our users. Every feature and improvement you develop will enhance customer choice and app performance, making it easier for users to find and enjoy the products they love. Your work will have a lasting impact on customer satisfaction and loyalty across diverse markets.

Responsibilities

• Ingesting first and third-party data sources into our databases.
• Curating and maintaining high-quality data assets so our data scientists can make informed decisions and create better products.
• Collaborating with cross-functional teams to deliver high-quality data assets.
• Deploying and maintaining ML models on our deployment framework.
• Architecting, defining, and building data pipelines to enable faster, better, data-informed decision-making.