Overview
In this role you will design, build, and maintain large-scale ML systems that price millions of opportunities per second in real-time. You will work with cross-functional teams to improve ML models and production pipelines, aiming to maximize advertiser outcomes. The role blends research and engineering, applying NLP, clustering, and LLMs to multi-language topics for targeted advertising. You’ll contribute to a high-velocity environment where scale and reliability are crucial, with mentorship from senior scientists and engineers.
Pay / Benefits
- competitive salary
- performance bonus
- equity
- comprehensive benefits package
Responsibilities
- Design, code, test, and debug ML applications for high-throughput systems
- Run ML experiments to validate modeling ideas
- Collaborate with senior scientists and engineers to iterate on models and practices
- Write clean, maintainable code and participate in code reviews
- Identify performance bottlenecks and optimize components for scalability
- Stay updated with ML developments and apply them to production
Key requirements
- 0-2 years of experience in ML or applied statistics (including internships or significant academic projects)
- Degree in Computer Science, Mathematics, Software Engineering, or adjacent field
- Fluency in Python or Java (or similar languages)
- Strong foundation in probability, statistics, and hypothesis testing
- Practical understanding of ML fundamentals (classification, regression, clustering, NLP/LLMs)
- Familiarity with data processing libraries (Pandas, NumPy) and ML frameworks (PyTorch, Scikit-learn, XGBoost)
- Interest in distributed systems, concurrent algorithms, data structures, and software engineering
- collaboration
- analytical rigor
- growth mindset
- Python
- Java
- Pandas
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