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.
- 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.
- Experience: 3+ 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.
- 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
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.
#LI-KW1
Viant Technology Inc. (NASDAQ: DSP) is a leader in CTV and AI-powered programmatic advertising, dedicated to driving innovation in digital marketing. Viant’s omnichannel platform built for CTV allows marketers to plan, execute and measure their campaigns with unmatched precision and efficiency. With the launch of ViantAI, Viant is building the future of fully autonomous advertising solutions, empowering advertisers to achieve their boldest goals. Viant was recently awarded Best AI-Powered Advertising Solution and Best Demand-Side Platform by MarTech Breakthrough, Great Place to Work® certification and received the Business Intelligence Group’s AI Excellence Award. Learn more at viantinc.com.
Top Skills
Similar Jobs
What you need to know about the Colorado Tech Scene
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute

.png)

