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An innovative company is seeking a Senior Machine Learning Systems Engineer to revolutionize programmatic TV. This role combines systems engineering with applied machine learning, focusing on optimizing intelligent bidding and campaign delivery. You'll collaborate with a dynamic team to build and deploy ML-powered systems using Zig and Python, ensuring efficiency in TV advertising. Join a fast-growing startup where your contributions will significantly impact the infrastructure of a cutting-edge CTV platform. If you're passionate about solving complex problems in a vibrant environment, this opportunity is for you.
Job Title: Senior Machine Learning Systems Engineer
Location: Remote, US
Department: Data Science
Type: Full-Time, Exempt
Experience: Senior (5+ Years)
Salary Range: $170,000 - $210,000 base
Core Hours: 9 AM - 1 PM PST / 12 - 4 PM EST
About tvScientific
tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.
Role Summary
We're looking for a Senior Machine Learning Systems Engineer to help push the boundaries of what's possible in programmatic TV. This role sits at the intersection of high-performance systems engineering and applied machine learning—and is core to how we scale intelligent bidding and campaign delivery across millions of TV screens. You'll work closely with our distributed team to optimize, build, and deploy ML-powered systems using Zig and Python, helping to make TV advertising as efficient and measurable as digital.
This is a unique opportunity to have outsized impact in a fast-growing Series B startup backed by top investors. If you thrive in fast-moving environments, love solving hard systems problems, and want to shape the infrastructure behind a next-gen CTV platform—this one's for you.
What You'll Do
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