Machine Learning Engineer

Magnetar•New York, NY

1d•Onsite

About The Position

Magnetar Capital, LLC seeks Machine Learning Engineer at its facility located at 10 E. 53rd Street, New York, NY 10022. Design, develop, and implement machine learning models and algorithms to automate various back-office processes. Engage in work that directly impact the efficiency of operations. Collaborate closely with our infrastructure engineers to ensure that solutions are scalable, secure, and integrated seamlessly into our existing systems. Develop and deploy machine learning models to automate back-office processes, such as trade reconciliation, reporting, compliance checks, and other operational tasks. Work closely with infrastructure engineers to integrate machine learning solutions with existing systems, ensuring scalability and security. Utilize Python, Snowflake, and Databricks to develop data pipelines, preprocess data, and implement machine learning algorithms. Continuously monitor and optimize machine learning models to improve accuracy and efficiency. Collaborate with cross-functional teams to identify areas where machine learning can add value and propose innovative solutions. Stay up to date with the latest advancements in machine learning and apply them to improve our processes. Up to 25% domestic travel required.

Requirements

Master’s degree, or foreign equivalent, in Computer Science, Data Science, Machine Learning, Information Engineering, or in a related field
2 years of experience as a Machine Learning Engineer, Software Engineer, or related occupation
Applying AI techniques to generate investment theses, automate workflows, and produce quantitative model signals
Performing sentiment analysis, conducting model fine-tuning and evaluation, and executing information extraction from unstructured text data
Designing and implementing algorithmic approaches that drive strategic decision-making and optimize investment performance
Constructing and managing robust data frameworks and pipelines to ensure efficient integration and accessibility of critical data
Developing and applying comprehensive models for investment analysis, risk assessment, and portfolio optimization

Responsibilities

Design, develop, and implement machine learning models and algorithms to automate various back-office processes.
Develop and deploy machine learning models to automate back-office processes, such as trade reconciliation, reporting, compliance checks, and other operational tasks.
Work closely with infrastructure engineers to integrate machine learning solutions with existing systems, ensuring scalability and security.
Utilize Python, Snowflake, and Databricks to develop data pipelines, preprocess data, and implement machine learning algorithms.
Continuously monitor and optimize machine learning models to improve accuracy and efficiency.
Collaborate with cross-functional teams to identify areas where machine learning can add value and propose innovative solutions.
Stay up to date with the latest advancements in machine learning and apply them to improve our processes.