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 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

• 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

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: $230,000 - $260,000 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.

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.