Staff Applied Scientist

<p><strong>WHAT YOU’LL DO</strong></p> <div> <div>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.</div> <div>&nbsp;</div> <div>We are seeking an exceptional Staff Applied Scientist to drive groundbreaking innovation in applied machine learning. In this role, you will lead end-to-end AI strategy, shape the applied science roadmap, and develop next-generation models in NLP, deep learning, and large-scale AI systems. Your expertise will push the boundaries of AI capabilities, delivering measurable business impact while fostering a research-driven, data-centric culture at Viant.</div> </div> <h3 data-qa="preview-list-item-0-text">THE DAY-TO-DAY</h3> <ul> <li>Lead and Define AI Strategy – Set the vision for applied ML research and AI-driven decision-making across Viant’s products and services.</li> <li>Drive High-Impact Research – Conduct advanced research in NLP, RL, LLMs, and deep learning, publishing in top-tier conferences while applying findings to real-world production systems.</li> <li>Architect and Deploy ML at Scale – Develop, optimize, and deploy high-throughput, low-latency ML models, collaborating with engineers to bring solutions into production.</li> <li>Innovate in Generative AI &amp; Causal ML – Explore novel AI techniques, such as LLMs, reinforcement learning, and causal inference, to enhance targeting, personalization, and attribution models.</li> <li>Experimentation and Validation – Design, run, and analyze A/B experiments to test ML-driven strategies, ensuring data-driven decision-making.</li> <li>Mentor and Influence – Provide technical leadership for a team of applied scientists and ML engineers, fostering a culture of innovation and excellence.</li> </ul> <h3 data-qa="preview-list-item-1-text">MUST HAVE</h3> <ul> <li>Experience: 4+ years of experience building and deploying machine learning models at scale.</li> <li>Technical Leadership: Demonstrated ability to lead complex, high-ambiguity ML projects from research to production.</li> <li>Academic &amp; Industry Recognition: Masters + At least two peer-reviewed publications in deep learning, NLP, or a related AI domain or a PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field.</li> <li>Deep Expertise in ML &amp; AI: Strong foundation in deep learning, NLP, generative AI, and causal inference.</li> <li>Programming &amp; Frameworks: Proficiency in Python and deep learning frameworks (TensorFlow, PyT