The Core Engineering, Machine Learning Engineer, New York, Vice President

Overview In this role, you will drive end-to-end ML projects at scale within Compliance Engineering, building and maintaining models that mitigate regulatory and reputational risk. You will collaborate with ML researchers and engineers to productionize AI solutions on big data platforms. You will shape infrastructure for feature engineering and scalable model deployment, iterating experiments to improve performance. This opportunity sits at the intersection of cutting-edge ML and risk management in a global, data-driven firm. Compensation / Benefitstraining and development opportunitieswellness programspersonal finance offeringsdiversity and inclusion initiativesglobal opportunitiesmindfulness programs Responsibilities Work with large-scale structured and unstructured data Lead end-to-end ML projects with high complexity Build ML infra including feature engineering and model scaling Develop, productionize, and maintain ML models Run experiments, tune features and models, document results Collaborate with ML researchers to accelerate model usage Perform code reviews and ensure code quality Key requirements Bachelor's or Master's degree in Computer Science or related field 10+ years of hands-on experience building scalable ML systems Strong coding fundamentals (algorithms, data structures, software design)Expertise in Python and PySpark Experience with distributed technologies (Scala, PySpark, Iceberg, HDFS, AWS/GCP) and big data feature engineering Experience in system design and data storage schemas Extensive experience with ML and DL tools (Tensor Flow, PyTorch, Scikit-Learn, Hugging Face)Desirable: experience with LLMs, prompt engineering, cloud deployments on AWS/GCP, distributed systems architecture reviewcollaboration across cross-functional teamscode reviews and mentoringdata-driven decision making Python PySpark Scala