Job description

WHAT YOU'LL DO The 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-DAY 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 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 models MUST 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 retraining A 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 above LIFE AT VIANT Investing 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: $225,000 - $275,000 In accordance with California law, the range provided is Viant’s reasonable estimate of the compensation for this role. Final title and compensation for the position will be based on several factors including work experience and education. #LI-AM1 About Viant Viant Technology (NASDAQ: DSP) is an exclusively buy-side, AI-powered advertising platform purpose-built for CTV. Viant uniquely combines proprietary content intelligence, household-level identity resolution, and person-level attention signals to connect advertisers with real customers and drive measurable outcomes across the open internet. Through its award-winning AI solutions, Viant is building the future of autonomous advertising, where AI doesn't just assist the campaign, it delivers real results. Learn more at viantinc.com. Viant is an equal opportunity employer and makes employment decisions on the basis of merit. Viant prohibits unlawful discrimination against employees or applicants based on race (including traits historically associated with race, such as hair texture and protective hairstyles), religion, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, reproductive health decision making, gender, gender identity, gender expression, age, military status, veteran status, uniformed service member status, sexual orientation, transgender identity, citizenship status, pregnancy, or any other consideration made unlawful by federal, state, or local laws. 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. By clicking “Apply for this Job” and providing any information, I accept the Viant California Personnel Privacy Notice.

Requirements

Must-haves

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 outcomes
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 models
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
Working fluency in the operational demands of production ML: delayed feedback, latency and serving tradeoffs, monitoring, drift, and retraining
A track record of technical leadership: reviewing and improving other scientists' system designs, not just managing their output
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 above

Nice-to-haves

Bachelor's degree in Computer Science, Engineering, or a related field; Master's preferred

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlai

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Health Insurance

Pto

Parental Leave