Machine Learning & Data Engineer

Job expired!

Machine Learning & Data Engineer Job Opportunity at CommentSold

About CommentSold

CommentSold is the leading North American provider of live selling technology, highly rated by G2. We have empowered over 7,000 small to mid-sized retailers with our state-of-the-art live-selling tools, facilitating the sale of more than 166 million items and generating over $3.8 billion in lifetime GMV. Our technology offers businesses and creators of all sizes unparalleled solutions for delivering engaging live video commerce experiences across multiple sales channels.

With our acquisition of Popshoplive's assets, CommentSold has expanded into direct-to-consumer commerce. Popshoplive is a community-driven livestream shopping marketplace that integrates social, e-commerce, and entertainment. In 2022, we launched Videeo, a lightweight video commerce plugin technology that allows any retailer or brand to embed and go live with engaging, branded live video commerce experiences within days, seamlessly integrating into their existing e-commerce stack.

About the Role: Machine Learning & Data Engineer

We are seeking a talented Machine Learning & Data Engineer to join our AI & Data Team. This critical role involves serving as a senior data engineering expert and cross-departmental liaison. Your primary responsibility will be to further develop our existing platforms, including both structured data warehouses and vast unstructured data lakes. This position is fully remote, based in Germany or India, with a requirement to work partially in EST or CST time zones in the US.

Main Responsibilities

  • As part of the AI & Data team, build a comprehensive company-wide data platform and drive data democracy and literacy within the company.
  • Develop and maintain the central data warehouse and its staging layers, oversee ingestion and ETL jobs to enable a seamless flow of structured data.
  • Scan internal and external data sources to propose extensions and updates for the data platform. Document data dictionary and ETL processes.
  • Own and upgrade the company's data lake in the cloud. Integrate event tracking and data off-loading into the data lake, including text, images, and video files. Ensure integrations with API gateways and down-streaming consuming services.
  • Design and manage API integrations and automated data robots for external data ingestion. Create internal API microservices to facilitate data exchange among products, systems, and third-party applications.
  • Dock machine learning and computer vision models into data pipelines, designing the data flow for these AI services.
  • Collaborate closely with engineering teams and other data team members to steer or support projects aimed at data tools and data product creation.
  • Interact with various stakeholders, including department leads and senior executives, to translate business needs into extensions or adaptations of our internal data troves.

Skills, Qualifications & Education

  • Bachelor’s degree in Computer Science, Machine Learning, or Artificial Intelligence.
  • At least 5 years of work experience in Business Intelligence, Data Analytics, or similar analytical roles.
  • Demonstrated aptitude for working with both structured and unstructured data, including troubleshooting failed ETL processes or API integrations.
  • Proficient in Python (especially for data handling).
  • Skills in Spark or TypeScript are a plus.
  • Strong expertise in SQL (tested during the recruitment process).
  • Well-versed in AWS cloud services, particularly AWS data handling services, and can navigate the interdependencies between individual components.
  • Hands-on experience with API implementation and data transfer.
  • Working knowledge of Machine Learning, NLP, and Computer Vision algorithms and solutions.
  • Experience with deep learning, GAI, and data crawling automation are a plus.
  • Outstanding data structure blueprinting skills.
  • Ability to effectively translate ideas between technical and non-technical audiences.
  • Solid business acumen and experience working with non-technical stakeholders or in e-commerce.
  • Collaborative team player, eager to share knowledge and exchange ideas with team members.
  • Curious, insights-driven, and thrivate on creating visible business impact.
  • Flexible, self-motivated, well-organized, and capable of managing multiple projects simultaneously, sometimes under tight deadlines.

Our Values

We’re building a community around a set of values that guide our work and interactions with the