21 hours ago
Taipei, TaiwanSenior
Responsibilities
- Design, develop, and deploy optimization solutions based on machine-learning models and evaluation methods.
- Partner with product managers and engineers to define problems, prioritize work, and integrate validated methods into products.
- Build reliable evaluation methods for LLM outputs and assess whether results apply to real-world conditions.
- Form hypotheses, design A/B tests using real traffic, interpret results, and own conclusions.
- Evaluate current research and industry solutions, recommend build-versus-adopt decisions, and propose new approaches.
- Monitor launched solutions and communicate risks, trade-offs, and progress.
- Optionally mentor junior scientists and interns.
Requirements
- Master’s or PhD degree in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or a related field.
- At least 2 years of experience in machine learning or engineering roles.
- Hands-on experience with classification, regression, ranking, retrieval, quality evaluation, and LLM-as-a-judge approaches.
- Solid statistics foundation and ability to connect technical methods to business impact.
- Ability to prioritize work, collaborate across functions, drive initiatives, and surface risks.
- Experience working daily with coding agents, reviewing their output, and correcting generated code.
- Preferred: project leadership, experimentation and A/B testing, embeddings, causal inference, and AI/LLM application engineering including serving and integration.
Categories
About Appier
Appier builds AI-driven advertising and marketing software for enterprises, offering programmatic ad bidding, customer data, and predictive tools delivered as SaaS. Founded in 2012 and headquartered in Taipei, it is a public company listed on the Tokyo Stock Exchange (ticker: 4180). Its Ad Cloud processes millions of bid requests per second across APAC, Europe, and the U.S., and is used by in-house and agency marketers.