We improve marketing performance with automated video mass-customization and testing.
Early market validation - running personalized video campaigns for Zappos and eBay.
Strong team - previously at Zazzle, leading ecommerce retailer using mass-customization; founded by friends from Cornell. Went through Facebook accelerator and Y Combinator.
Well-positioned - at the intersection of video, personalization, and AI-driven optimization; 3 megatrends that will shape the marketing tech landscape in the years to come.
The engineering team at Indivio is still a small group leveraging prior experiences from a fast growing software startup as well as from a background in semiconductor manufacturing. We set quarterly goals and plan our execution weekly to stay nimble and responsive to the market needs. We’ve adopted the good parts of agile development and try not to get tied up in process while we’re still a small team. We huddle daily and demo weekly to stay informed and consistently do retrospectives to keep asking ourselves how we can perform better as a team. We emphasize writing requirements ahead of code because that’s usually the harder part of building a feature. We spike frequently to explore the unknowns or to try something new. We do code reviews to ensure knowledge is distributed throughout the team. We try to test rigorously while striking the right balance with moving fast.
At Indivio, we’re building software and automation for marketers as well as creatives. The system accepts video templates as inputs from creatives, which can be connected to data sources from marketers to generate video variations on demand. We analyze and optimize the videos with ML/AI to meet the various marketing objects. Our frontend presents a simple workflow to connect the data, preview videos, and analyze the video performance. Our API backend handles the on demand distributed computing required to prepare the data as well as to render the video variations. In addition to the compute intensive challenges with rendering videos, our data pipeline synchronizes with data sources, for example by scraping every single product on an ecommerce site or applying image processing and NLP to ensure the resulting videos are visually appealing with minimal human interaction.
As a Backend engineer, you may be tasked with building a worker status & control module, which can present the status of all distributed workflow machines at any given time, automatically analyze and predict weak points in the workflow that require preventative maintenance, and intelligently implement preventative maintenance algorithms to maximize overall worker uptime while minimizing task failures. This process should include a requirements document which describes the different distributed workers in the system, their potential points of failure, and how to report and recover them. Implementation will start as standalone modules followed by a comprehensive management console. This module will be responsible for the visibility and maintainability of hundreds of distributed Linux and Windows workers with multiple cloud platforms.
As a Frontend engineer, you may be tasked with building a new user workflow that allows marketers to publish and optimize videos on a new advertising platform, such as Snapchat. You’ll start with written requirements and UI mocks for the new workflow in Confluence and Sketch, while clarifying the API dependencies with both Snapchat and Indivio. As you implement the code, you may initially have mocked backend responses to build against, but eventually would integrate with the backend to complete the feature.
We value can-do attitudes, customer-orientation, teamwork, resourcefulness, initiative, and thoughtful risk-taking. We work hard, play hard, and try to be respectful of work/life balance because this is a marathon.
daily lunch if in the office, light snacks
preference is in office, but some flexibility here if required
We try to have a couple of team outings a quarter to meals or events.
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