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
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