Senior Machine Learning Scientist, Playable Ads

About this role

<p><strong>About Appier </strong></p> <p>Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of “Making AI Easy by Making Software Intelligent,” Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at<a href="http://www.appier.com/" target="_blank" data-saferedirecturl="https://www.google.com/url?q=http://www.appier.com/&source=gmail&ust=1772524763166000&usg=AOvVaw2VstxLR9Gjx8R3vPf40kL6"> </a><a href="https://www.appier.com">www.appier.com</a>.</p> <p> </p> <p><strong>About the role</strong></p> <p>AI is reshaping how brands connect with consumers — and at Appier, we’re at the forefront. Our Playable Ads team builds AI-powered ad experiences — from interactive playable formats to video ads — that drive dramatically higher engagement and conversion for the world’s leading apps and games. We’re looking for a Senior Machine Learning Scientist to push the boundaries of what’s possible — applying cutting-edge ML, generative AI, and optimization techniques to create smarter, more compelling ad creatives at scale.</p> <p>If you’re excited about turning the latest advances in AI into products that reach millions of users, and you thrive at the intersection of research and real-world impact, we’d love to talk.</p> <p> </p> <p><strong>What You’ll Work On</strong></p> <ul> <li>Apply ML and generative AI techniques to problems such as creative optimization, user behavior prediction, engagement modeling, and dynamic content generation for various creative formats.</li> <li>Own the end-to-end ML lifecycle — from problem framing and experimentation through to production deployment and continuous improvement.</li> <li>Collaborate closely with product, engineering, and design teams to translate business goals into well-defined ML solutions.</li> <li>Conduct offline and online evaluation, A/B testing, and performance monitoring to continuously improve model quality and business impact.</li> <li>Stay current with the latest research in areas like LLMs, multimodal models, reinforcement learning, and recommendation systems, and proactively propose innovative applications to the team.</li> <li>Mentor fellow scientists and contribute to the team’s technical standards and culture.</li> </ul> <p><br><strong>What We’re Looking For</strong></p> <p>[Minimum qualifications]</p> <ul> <li>Master’s or Ph.D. in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or a related field.</li> <li>Solid understanding of <strong>modern ML models and algorithms</strong>, with hands-on experience in at least one area such as prediction/optimization, generative models, recommendation systems, computer vision, or reinforcement learning.</li> <li>Proficient in <strong>Python</strong> and ML frameworks such as PyTorch or TensorFlow.</li> <li>Practical experience taking ML models from prototype to production, including pipeline development and performance monitoring.</li> <li>Strong analytical and problem-solving skills with the ability to diagnose model behavior and improve training pipelines.</li> <li>Clear communicator who can explain technical ideas to both technical and non-technical stakeholders and enjoys working in a fast-paced, collaborative environment.</li> <li>Proficient in using LLM-powered development tools (e.g., GitHub Copilot, Cursor, ChatGPT) to accelerate productivity.</li> <li>Ability to balance cutting-edge research with time-to-market constraints, delivering iterative PoCs that validate product hypotheses and translate into production-ready solutions.</li> </ul> <p>[Preferred qualifications]</p> <ul> <li>Publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, KDD, RecSys).</li> <li>Experience in the advertising technology or MarTech domain.</li> <li>Contributions to open-source projects or active involvement in research communities.</li> </ul> <p> </p> <p>#LI-AK1</p>