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2026 MIT- Machine Learning Researcher Interns

BostonHybridPart-time

AI Summary

Internship focusing on machine learning research across areas like time series forecasting, deep learning, NLP, and privacy. Supports research on theoretical and applied ML projects with potential to publish at top conferences.

About this role

What's the opportunity?

RBC Borealis is the driving force behind Royal Bank of Canada’s AI and data innovation. As part of Canada’s largest financial institution, we bring together a team of architects, engineers, scientists, and product experts on a mission to revolutionize finance through world-class research, solutions, and a resilient data platform. With locations across Toronto, Waterloo, Montreal, Calgary, and Vancouver, we’re at the forefront of AI research and platform development. With a focus on cutting-edge research in areas like time series forecasting, causal machine learning, and responsible AI, we are seamlessly integrating AI research and data engineering, to solve critical challenges in the financial industry. We are building intelligent, and scalable, data-driven solutions that will help communities thrive and drive innovation for our customers across the bank.

We offer a hybrid working model for our internship program. Interns will support research on a diverse range of theoretical and applied machine learning projects. By working at RBC Borealis, you will gain unique access to extensive structured and unstructured datasets, along with the tools and resources needed to develop groundbreaking statistical models. Being part of our team will provide you with the opportunity to publish original research at respected peer-reviewed academic conferences, such as NeurIPS, ICLR, ICML, and CVPR.

Internship opportunities are available in the following areas:

  • AutoML;
  • Bayesian Optimization;
  • Computer Vision;
  • Deep Learning;
  • Generative AI;
  • Graphs and Optimization;
  • Interpretability and Explainability;
  • Natural Language Processing;
  • Privacy and Fairness;
  • Reinforcement Learning;
  • Time Series Forecasting;
  • Unsupervised and Semi-supervised Learning.

You're our ideal candidate if you have:

  • Pursuing a graduate degree in Computer Science, Engineering or another mathematically related field (e.g., Physics, Math, Statistics, etc.)
  • Previous publications at a top-tier AI conference;
  • Proficient with writing modular, robust, scalable software in Python;
  • Experience with data processing frameworks such as Tensorflow, Keras, and PyTorch;
  • Experience with building and deploying machine learning algorithms and/or statistical modeling;
  • Previous experience with the Unix command line and bash scripting;
  • A deep understanding of machine learning algorithms and/or statistical modeling;
  • Ability to implement state-of-the-art machine learning techniques;
  • High motivation to solve challenging research problems;
  • Passion for data, algorithms, and statistics.

Internship Duration:

4 months (September 2nd to December 18th, 2026)

Inclusion and Equal Opportunity Employment

At RBC, we embrace diversity and inclusion for innovation and growth. We are committed to building inclusive teams and an equitable workplace for our employees to bring their true selves to work. We are taking actions to tackle issues of inequity and systemic bias to support our diverse talent, clients and communities.

We also strive to provide an accessible candidate experience for our prospective employees with different abilities. Please let us know if you need any accommodations during the recruitment process.

Skills

Bash ScriptingData Processing FrameworksKerasMachine Learning AlgorithmsPythonPyTorchSoftware DevelopmentStatistical ModelingTensorFlowUnix Command Line

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