Machine Learning Engineer (MLE) Intern

DRW

Mar 29

Applications are closed

Internship
Full-time
Summer Internship
Data
Chicago

Requirements

A degree in Computer Science, Data Science, Engineering, or a related field graduating between December 2024 and June 2025 (Bachelor’s, Master’s)
Strong foundation in machine learning concepts (supervised/unsupervised learning, classification, regression).
Solid understanding of NLP fundamentals and experience with LLMs a plus.
Proficiency in Python programming and familiarity with libraries like NumPy, Pandas, and Scikit-learn.
Excellent analytical, problem-solving, and communication skills.
Passion for developing innovative AI solutions within the financial domain.
Preferred Skills:
Experience with NLP tasks (text classification, summarization, question-answering).
Knowledge of TensorFlow or PyTorch.
Basic understanding of MLOps principles (monitoring, versioning, model serving).
Learning Opportunities:
Gain in-depth experience with cutting-edge NLP techniques, effective LLM utilization, and model deployment in a real-world setting.
Develop robust MLE skills, from data engineering to model evaluation, while directly influencing the growth of the SWE environment.
Contribute to projects with direct impact on financial decision-making.
Be a part of building a strong software engineering culture, driving improvements in code quality, collaboration, and efficiency.

Responsibilities

Model Development & Refinement: Design, implement, and refine NLP models for financial applications, leveraging LLM capabilities and collaborating to improve software engineering practices.
Prompt Engineering: Develop and optimize prompts for more effective interaction with LLMs, tailored to finance-specific tasks, in alignment with evolving SWE methodologies.
Data Engineering: Participate in building data pipelines for model training and evaluation, including data collection, cleaning, preprocessing, and labeling, while contributing to better data management.
Model Testing & Evaluation: Design and implement rigorous testing frameworks to assess NLP model performance and identify areas for improvement.
Python Development: Write efficient Python scripts for data manipulation, model training, and model deployment, with a focus on code quality and maintainability.
SWE Collaboration: Work closely with the team to establish and refine software engineering practices, promoting code reviews, testing, and documentation.
Research & Learning: Stay updated on the latest NLP and MLOps techniques, share insights and actively bring improvements to development processes

DRW

Finance

Industry

1001-5000

Employees

Mission & Purpose

At DRW, we identify and capture trading and investment opportunities globally. What sets us apart is our diversified approach—trading across many asset classes and instruments, in markets around the world, with horizons from seconds to years. We succeed by leveraging technology, research and risk management. We offer the best of both worlds: the opportunity and spirit of a startup and the benefits and stability of an established, experienced firm. Our employees work hard to solve interesting problems, and their results are rewarded. We value continuous learning—from our outcomes, from the environment and from each other. It’s a place of high expectations, deep curiosity, and constant collaboration, with some of the smartest, most passionate people you’ll meet.