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A leading technology company in Canada seeks a Senior/Staff Applied Machine Learning Scientist to join their engineering team. The role involves leading the optimization of machine learning algorithms, developing production-grade models, and driving innovative data testing. Candidates should have a master's degree or PhD and at least 3 years of relevant experience. Competitive salary and comprehensive health benefits offered, alongside a supportive and inclusive work culture.
Canada
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 are searching for a talented Senior or Staff Applied Machine Learning Scientist tto join our engineering team as we continue to expand our data science efforts. Our platform is connected to thousands of publishers and advertisers worldwide and as a result, we’re dealing with millions of requests each second, making billions of decisions. We utilize the latest technologies to solve challenges in traffic, data storage, machine learning, and scalability.
StackAdapt is a remote‑first company, and we are open to candidates located anywhere in the US or Canada for this position.
StackAdapt is a diverse and inclusive team of collaborative, hardworking individuals trying to make a dent in the universe. No matter who you are, where you are from, who you love, follow in faith, disability (or superpower) status, ethnicity, or the gender you identify with (if you’re comfortable, let us know your pronouns), you are welcome at StackAdapt. If you have any requests or requirements to support you throughout any part of the interview process, please let our Talent team know.
About StackAdapt
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