Machine Learning Engineer

b Overview /b p 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. /p b Pay / Benefits /b ul li competitive salary /li li performance bonus /li li equity /li li comprehensive benefits package /li /ul b Responsibilities /b ul li Design, code, test, and debug ML applications for high-throughput systems /li li Run ML experiments to validate modeling ideas /li li Collaborate with senior scientists and engineers to iterate on models and practices /li li Write clean, maintainable code and participate in code reviews /li li Identify performance bottlenecks and optimize components for scalability /li li Stay updated with ML developments and apply them to production /li /ul b Key requirements /b ul li 0-2 years of experience in ML or applied statistics (including internships or significant academic projects) /li li Degree in Computer Science, Mathematics, Software Engineering, or adjacent field /li li Fluency in Python or Java (or similar languages) /li li Strong foundation in probability, statistics, and hypothesis testing /li li Practical understanding of ML fundamentals (classification, regression, clustering, NLP/LLMs) /li li Familiarity with data processing libraries (Pandas, NumPy) and ML frameworks (PyTorch, Scikit-learn, XGBoost) /li li Interest in distributed systems, concurrent algorithms, data structures, and software engineering /li /ul ul li collaboration /li li analytical rigor /li li growth mindset /li li Python /li li Java /li li Pandas /li /ul