stackadapt · Alberta, Canada; British Columbia; Calgary, Alberta, Canada; California; New York; Ontario; Seattle; Toronto; Vancouver; Washington
StackAdapt is the leading technology company that empowers marketers to reach, engage, and convert audiences with precision. With 465 billion automated optimizations per second, the AI-powered StackAdapt Marketing Platform seamlessly connects brand and performance marketing to drive measurable results across the entire customer journey. The most forward-thinking marketers choose StackAdapt to orchestrate high-impact campaigns across programmatic advertising and marketing channels. We're looking to add a Machine Learning Engineer to our Data Science team! This team works on solving complex problems for StackAdapt's digital advertising platform. You'll be working directly with our Applied Machine Learning Scientists, Machine Learning Engineers, Engineering teams, and our CTO/Co-Founder on building pipelines and ad optimization models. With databases that process millions of requests per second, there's no shortage of data and problems to tackle. StackAdapt is a remote-first company with teams around the world. Our teams work in a fully distributed environment, and we are open to candidates based in Canada and the United States. Want to learn more about our Data Science Team: https://alldus.com/ie/blog/podcasts/aiinaction-ned-dimitrov-stackadapt/ Learn more about our team culture here: https://www.stackadapt.com/careers/data-science Watch our talk at Amazon Tech Talks: https://www.youtube.com/watch?v=lRqu-a4gPuU What you'll be doing: Design modular and scalable real time data pipelines to handle huge datasets Understand and implement custom ML algorithms in a low latency environment Work on microservice architectures that run training, inference, and monitoring on thousands of ML models concurrently What you'll bring to the table: Have the ability to take an ambiguously defined task, and break it down into actionable steps Have deep understanding of algorithm and software design, concurrency, and data structures Experience in implementing probabilistic or machine learn…
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