Director, Applied Science - Ad Optimization & ML Systems
Own the end-to-end design, deployment, and performance of Viant's real-time prediction and bid-optimization systems — models that run inside strict latency budgets and directly drive auction outcomesDefine the technical formulation for ambiguous ad-optimization problems: what's being optimized (click, conversion, ROAS, or incremental value), who the valid training population is, what the model should predict, and how a downstream system should interpret itProvide technical and strategic leadership to a team of applied scientists and ML engineers — reviewing designs, coaching through production tradeoffs, and setting technical directionOwn the operational realities of production ML at scale: delayed feedback and attribution, label imbalance, latency and serving constraints, monitoring, drift, and retrainingEvaluate and improve the systems that decide how bids are placed and adjusted in live auctions, incorporating budget, volume, and business constraints into the model's outputCollaborate with Product and Engineering leadership to align technical roadmap with business prioritiesBuild toward more autonomous, multi-step decisioning systems as the team's technical roadmap expands beyond single-prediction modelsMUST HAVE 10+ years of experience building and deploying production machine learning systems, with at least 5+ years in a hands-on technical leadership roleDirect experience with real-time, high-scale decisioning systems — ad optimization, bidding, ranking, recommendation, or a closely comparable domain with similar latency and volume constraintsDemonstrated ability to formulate an ambiguous business problem into a precise ML specification: labels, training population, objective, loss function, and evaluation metrics — without relying on framework-level generalitiesWorking fluency in the operational demands of production ML: delayed feedback, latency and serving tradeoffs, monitoring, drift, and retrainingA track record of technical leadership: reviewing and improving other scientists' system designs, not just managing their outputBachelor's degree in Computer Science, Engineering, or a related field; Master's preferredGREAT TO HAVE Direct experience with real-time bidding, ad auctions, or programmatic advertising systems specificallyExperience with identity resolution or cross-device/cross-platform user matchingExperience with agentic or multi-step autonomous decisioning systemsPhD in Machine Learning, Computer Science, or a related fieldPublications or conference contributions in ML or a closely related fieldFormal people-management tenure beyond the 5-year hands-on leadership requirement aboveLIFE AT VIANTInvesting in our employee’s professional growth is important to us, but so is investing in their well-being. Final title and compensation for the position will be based on several factors including work experience and education.#LI-AM1 Viant also prohibits unlawful discrimination based on the perception that anyone has any of those characteristics, or is associated with a person who has or is perceived as having any of those characteristics.