Qualifications
Key Responsibilities:Develop production-grade Python code that supports real-time bidding, model training, and campaign optimization. Train, deploy, and supervise machine learning models that determine which ads to display, timing, and pricing—processing millions of bid decisions per second. Enhance our incrementality measurement systems to assist advertisers in grasping the genuine causal impact of their CTV investments. Design and introduce new machine learning products throughout the ad-buying lifecycle, including audience targeting, bid optimization, pacing, and attribution. Leverage large language models (LLMs) and generative AI to create internal tools that expedite the development, testing, and deployment of machine learning systems. Act as a technical leader and mentor within a distributed engineering team. Desired Qualifications:Proficient in production Python programming: capable of writing code that operates in production environments. Strong grasp of statistical principles and machine learning fundamentals: able to analyze experimental designs, model evaluations, and when to opt for simpler methods over complex ones. Familiarity with contemporary AI tools and a keen sense of where they can add value. Experience in adtech or CTV, with knowledge of real-time bidding, programmatic advertising, and supply-path optimization. Excellent written communication skills: vital for decision-making in our distributed team. Ability to navigate ambiguity: you will be responsible for end-to-end problem ownership in a dynamic environment, from scoping to delivery.
About the job
About tvScientific
tvScientific stands as the pioneering CTV advertising platform meticulously designed for performance marketers. By harnessing extensive datasets and advanced scientific methodologies, we automate and refine TV advertising to achieve measurable business results. Our comprehensive solution integrates media buying, optimization, measurement, and attribution into a streamlined platform. Developed by industry veterans with a robust background in programmatic advertising, digital media, and ad verification, our platform offers a reliable CTV performance solution that empowers advertisers to elevate their business.
As a Senior Machine Learning Engineer at tvScientific, you will be instrumental in building the machine learning and AI systems that underpin our Connected TV ad-buying platform, focusing on real-time bidding, campaign optimization, and incremental measurement at scale. As an adtech innovator, we are tackling the complex challenge of making CTV advertising quantifiable. Our platform enables advertisers to purchase ads across a diverse CTV ecosystem—including Hulu, Pluto TV, Disney+, HBO Max, and numerous FAST channels—while demonstrating that these ads generate tangible business results.
About tvScientific powered by Pinterest
tvScientific is at the forefront of transforming CTV advertising into a powerful tool for performance marketers. Our platform is designed to streamline and optimize advertising efforts, ensuring that advertisers can effectively measure the impact of their campaigns across a multitude of channels. With a foundation built on industry expertise and innovative technology, we are dedicated to delivering results that matter to our clients.