Director, Real-Time ML & Ad Optimization

VIANT TECHNOLOGY; Irvine (CA); On-site; USD 230,000 - 260,000; Full time

Benefits offered by this job

Fully paid health insurance

Paid parental leave

Unlimited PTO

Job summary

Viant Technology in Irvine, CA is seeking a Director of Applied Science to own end-to-end ad optimization and ML systems in real time, leading a team of applied scientists and ML engineers while also contributing hands-on.

You will define problem formulations, oversee production ML at scale, manage latency, monitoring, retraining, and collaborate with product and engineering to align technical roadmap with business goals.

Qualifications

• 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, or similar latency/volume constraints.
• Ability to formulate an ambiguous business problem into a precise ML specification (labels, training population, objective, loss function, evaluation metrics).
• Operational fluency with production ML: delayed feedback, latency tradeoffs, monitoring, drift, retraining.

Responsibilities

• Own end-to-end design, deployment, and performance of real-time prediction and bid-optimization systems.
• Define technical formulation for ad-optimization problems and interpretations for downstream systems.
• Provide technical leadership and coaching to a team of scientists and ML engineers.
• Oversee production ML at scale, including latency, serving constraints, drift, and retraining.
• Collaborate with Product and Engineering to align technical roadmap with business priorities.
• Progress toward autonomous, multi-step decisioning systems as the roadmap expands.

Skills

Real-time ML systems

Technical leadership

Production ML

ML model deployment

Education

Bachelor's in CS/Engineering

Master's preferred

PhD (bonus)

Job description

Viant Technology in Irvine, CA is seeking a Director of Applied Science to own end-to-end ad optimization and ML systems in real time, leading a team of applied scientists and ML engineers while also contributing hands-on.

You will define problem formulations, oversee production ML at scale, manage latency, monitoring, retraining, and collaborate with product and engineering to align technical roadmap with business goals.