Director, Applied Science - Ad Optimization & ML Systems

WHAT YOU'LL DOThe Machine Learning team at Viant builds the real-time decisioning systems that power programmatic advertising — models that predict, in milliseconds, whether an ad opportunity is worth bidding on, and systems that decide how much to bid, live, across billions of auctions.

We're looking for an experienced Director of Applied Science to own this technical domain end to end: the models, the production systems they run on, and the team that builds them. This is a hands-on, player-coach role — you'll review designs, unblock scientists on hard formulation problems, and still be able to work through the math and the system tradeoffs yourself when it matters.

THE DAY-TO-DAYOwn 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 outcomes

Define 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 it Provide technical and strategic leadership to a team of applied scientists and ML engineers — reviewing designs, coaching through production tradeoffs, and setting technical direction

Own the operational realities of production ML at scale: delayed feedback and attribution, label imbalance, latency and serving constraints, monitoring, drift, and retraining

Evaluate 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 output

Collaborate with Product and Engineering leadership to align technical roadmap with business priorities

Build 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 role Direct experience with real-time, high-scale decisioning systems — ad optimization, bidding, ranking, recommendation, or a closely comparable domain with similar latency and volume constraints

Demonstrated 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 generalities

Working 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 output

Bachelor's degree in Computer Science, Engineering, or a related field;
Master's preferred GREAT TO HAVE Direct experience with real-time bidding, ad auctions, or programmatic advertising systems specifically

Experience with identity resolution or cross-device/cross-platform user matching

Experience with agentic or multi-step autonomous decisioning systems

PhD in Machine Learning, Computer Science, or a related field

Publications or conference contributions in ML or a closely related field

Formal 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. That’s why Viant was voted one of the best places to work and some of our favorite employee benefits include fully paid health insurance, paid parental leave and unlimited PTO and more. Base compensation range: $230,000 - $260,000

In accordance with California law, the range provided is Viant’s…