About the Role
The NEXT Quality (NQ) team at Moloco focuses on the operation and optimization of software systems and ML modeling, working closely with infrastructure engineering teams and Machine Learning Engineers. As an Applied Scientist II, you will contribute to driving performance improvements and cost reductions by debugging and investigating production issues and stabilizing the core system through deep end-to-end understanding.
Responsibilities
- Lead research projects, possibly with a small team of applied scientists, as part of a group of cross-functional collaborators to evaluate the health of both internal and external components to ensure the Moloco system is running safely and efficiently.
- Collaborate with your team to identify areas for infrastructure and machine learning component improvements by analyzing internal system changes, external changes, and data changes.
- Lead your project and contribute directly to deep, unbiased analysis, always driving to the actual root causes of issues.
- Participate in the design, implementation, and evaluation of new algorithms and features in collaboration with Software Engineers and Machine Learning Engineers.
Requirements
- Ph.D. in Computer Science, Mathematics, or a related field (new graduates welcome), or a Master’s or Bachelor’s degree with 2+ years of industry or postgraduate research experience in a quantitative or ML-related discipline.
- 2+ years of experience working on research-oriented projects involving machine learning, optimization, statistics, or large-scale data analysis.
- Experience contributing to research or modeling projects, ideally in collaboration with data scientists, machine learning engineers, or software engineers.
- Proficient verbal and written English communication skills, with the ability to present information and analysis results to collaborators and occasionally to larger groups.
- Quick understanding of new information and the demonstrated ability to learn new technical skills across engineering, machine learning, and data science.
- Track record of building positive relationships with collaborators and stakeholders and working effectively with cross-functional partners in a global company.
- Strong intellectual curiosity with a passion for exploring new ideas, identifying novel approaches, and continuously improving methodologies.
- Highly self-motivated and proactive, with the ability to drive research projects forward independently while maintaining alignment with team goals.