AI/ML Research Intern

DRWMontreal, QC

About The Position

As an AI/ML Research Intern, you will be an integral member of a team of experienced technologists, quantitative researchers, and traders. You will collaborate closely with other researchers to solve challenging AI and machine learning problems. Your projects will vary depending on priorities at the start of your employment and could include solving forecasting problems or developing large language models (LLMs). We are looking for individuals eager to learn new AI technologies, create innovative solutions, and choose the right tools to directly impact our business. You will be surrounded by cutting-edge technology, given immediate responsibility, mentored by industry-leading experts, and attend a robust training program to ensure your success at DRW.

Requirements

  • Pursuing a master’s, or PhD (preferred) degree in a technical discipline focusing on machine learning, deep learning or NLP graduating between December 2027 and June 2028
  • Expertise in deep learning, machine learning and statistics
  • Demonstrated experience training large models
  • Good knowledge of deep learning tools and packages such as Tensorflow, Pytorch, Keras, scikit-learn
  • Experience programming in Python
  • Experience with scripting
  • Strong communication skills to advocate your ideas in a clear and concise manner to the team
  • Positive, team-oriented attitude

Nice To Haves

  • Software best practices (agile, version control, experiment tracking, code review etc.)
  • Publications in relevant conferences and journals

Responsibilities

  • Designing and implementing large scale deep learning models for computer vision, reinforcement learning, graph neural networks or similar domain
  • Improving our data and data pipelines
  • Time series forecasting
  • Applying deep learning methods to telemetry data (sensor data and metrics collected from intelligent devices)

Benefits

  • Housing: DRW provides fully furnished apartments located close to the office
  • Mentorship
  • Education: options course framed from a developer’s standpoint
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