Senior Research Engineer - Capital Markets

What’s the opportunity?

Borealis AI is looking for an enthusiastic Senior Research Engineer who’s excited by the opportunity of being at the forefront of machine learning technology, and working on extremely challenging problems in the financial services industry. As a Senior Research Engineer, you’ll be part of a collaborative team delivering AI projects end to end – everything from scoping and defining the AI problem, to data pre-processing and exploration, to prototyping novel algorithmic solutions, to software implementations of machine learning-based products. At Borealis AI, you’ll be joining a team that works directly with leading researchers in machine learning, have access to rich and massive datasets, and offers the computational resources to support cutting-edge machine learning R&D.

Your responsibilities include:

  • Providing technical leadership throughout the research and product development lifecycle to deliver cutting edge AI solutions;
  • Partnering with Borealis AI’s business, product, research, and engineering teams to ensure the seamless delivery of these products;
  • Collaborating with business stakeholders to define the AI problem and rapidly prototype a solution;
  • Engaging in applied research experimentation to build and improve upon algorithms and models used in Borealis AI’s products;
  • Supporting projects with thorough documentation, design decisions, and technical advisory.

You’re our ideal candidate if you have:

  • Ability to independently drive the ML research process, including engineering novel relevant features, integrating mixed data sources, applying off-the-shelf ML models when appropriate, and inventing/developing new ML models when necessary;
  • Ability to approximate real-world business concepts with mathematical models and leverage those models to drive ML design process;
  • Ability to manage large numbers of ML experiments across shared resources;
  • Proficient in Python, data science tooling, and deep learning frameworks;
  • Firm grasp of the ML modelling process, including underfitting/overfitting, regularization, and different loss functions and model selection metrics and their tradeoffs;
  • Ability to collaborate with colleagues spanning a mix of business, product, engineering, and research teams through both written and oral communications.

Any of these additional skills would also be helpful in this role:

  • Familiarity with a wide variety of (deep and classical) ML methods, including an understanding of different models’ pros and cons;
  • Familiarity with feature importance methods;
  • Experience with automated ML methods;
  • Experience monitoring and maintaining a production ML system operating continuously in real time;
  • Experience working with time series data, especially highly stochastic and/or non-stationary processes;
  • Experience with signal processing and/or understanding of information theory;
  • Experience with statistical hypothesis testing, scientific experimental techniques, A/B testing, or similar;
  • Experience with algorithmic trading, KDB/q, price prediction/alpha generation, or financial machine learning.

What’s in it for you?

  • Be part of a dynamic & flexible working environment;
  • Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;
  • A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, and stock options where applicable;
  • Leaders who support your development through coaching and managing opportunities;
  • Ability to make a difference and lasting impact from a local-to-global scale.

About Borealis AI

Borealis AI, a RBC Institute for Research, is a curiosity-driven research centre
dedicated to achieving state-of-the-art in machine learning. Established in 2016,
and with labs in Toronto, Montreal, Waterloo and Vancouver, we support academic
collaborations and partner with world-class research centres in artificial intelligence.
With a focus on ethical AI that will help communities thrive, our machine learning
scientists perform fundamental and applied research in areas such as reinforcement
learning, natural language processing, deep learning, and unsupervised learning to
solve ground-breaking problems in diverse fields.

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.

 

Ready to Apply?