Senior Applied Scientist

Viant Technology•Los Angeles, CA

1d•$160,000 - $200,000

About The Position

WHAT YOU’LL DO Viant’s Machine Learning team is at the forefront of transforming the Ad Tech industry through cutting-edge machine learning and AI-driven automation. By eliminating manual processes in digital ad creation, optimization, and measurement, we build autonomous, scalable systems that process hundreds of millions of events daily. We are seeking a high-potential Senior Applied Scientist (Early Career) to contribute to the development of next-generation machine learning models across optimization, targeting, and measurement systems. In this role, you will work closely with senior scientists and engineers to design, experiment with, and deploy ML solutions that drive measurable business impact. This is an opportunity to apply strong research foundations to real-world production systems at scale while growing into a technical leader within the organization.

Requirements

Experience: 1-2 years of experience building machine learning models OR recent PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field
Strong ML Foundations – Solid understanding of: Supervised and unsupervised learning, Statistical modeling, Optimization methods, Model evaluation and validation.
Programming Skills: Proficiency in Python and familiarity with ML frameworks such as PyTorch, TensorFlow, or similar.
Data & Experimentation Skills – Experience working with structured datasets and conducting rigorous experimental analysis.
Problem-Solving Ability – Ability to break down ambiguous problems and develop practical modeling approaches with guidance.

Nice To Haves

Research experience in deep learning, NLP, reinforcement learning, or causal inference
Internship or industry experience deploying ML models
Experience with SQL and large-scale datasets
Exposure to cloud environments (AWS, GCP, Azure)
Interest in Ad Tech, real-time systems, or large-scale personalization

Responsibilities

Develop & Evaluate ML Models – Contribute to the design, implementation, and evaluation of machine learning models across areas such as NLP, deep learning, optimization, and personalization.
Collaborate on Production Systems – Partner with engineers to help deploy and monitor models in large-scale, real-time environments.
Experimentation & Analysis – Design and analyze A/B experiments to evaluate model performance and support data-driven decision-making.
Research & Innovation – Stay current with advances in ML and AI, applying modern techniques to practical advertising and measurement challenges.
Cross-Functional Collaboration – Work closely with Product, Engineering, and Data teams to translate business problems into scalable modeling solutions.
Continuous Learning & Growth – Receive mentorship from senior scientists while building technical depth in production ML systems.