At Borealis AI, you’ll be joining a team of leading researchers and software engineering specializing in machine learning. You will have have access to rich and massive datasets, and to computational resources to support novel product development touching machine learning areas such as reinforcement learning, natural language processing and time series analysis.

We’re looking for an enthusiastic scientists or software developer who’s excited by the opportunity of being at the forefront of applying machine learning technology to challenging problems. As a Research Engineer in the incubator team, you’ll be part of a collaborative group who aims to deliver AI projects end to end – everything from data pre-processing and exploration, to prototyping novel algorithmic solutions, to software implementations of machine learning-based products. The incubator’s goal is to understand the needs of our business partners and bring to life these unique and efficient solutions that can only be achieved through the use of machine learning.

With a focus on Capital markets, you will strive by digging and linking the intricacies of financial models with novel machine learning techniques. Our team performs research and product development on a wide variety of theoretical and applied machine learning projects in the space that spans domain such as forecasting, natural language processing, optimal control with reinforcement learning and synthetic data generation.
Working in capital markets will grant you unique access to work with top quantitative analysts, and the resources necessary to drive your product vision. This means you’ll also have the opportunity to innovate, and contribute to, the novel machine learning ideas that will be transformative to this line of business in the near future.

Your responsibilities include:

• Building machine learning-based software solutions;
• Collaborating with business stakeholders to prototype machine-learning solutions rapidly;
• Conducting comparisons to existing algorithms and baselines;
• Reviewing, extending, and optimizing prototype solutions;
• Collaborating with the engineering team to integrate algorithms into products;
• Developing reusable internal tools to facilitate research prototyping; and
• Supporting projects with thorough documentation, design decisions, and capabilities.

You’re our ideal candidate if you have:

• A master’s or PhD degree in computer science, mathematics, physics, economics or equivalent;
• 2+ years of applied machine learning experience in a high-responsibility, minimal-supervision environment;
• Experience with writing modular, robust, scalable software in Python 3.x;
• Expertise in a few of the following areas: deep learning, time series, forecasting, natural language processing, financial modelling, causality, explainability;
• Experience or an interest in quantitative finance;
• Experience with deep learning packages such as PyTorch, JAX, or Tensorflow;
• Knowledge of professional software engineering best practices for the full software development life cycle, including testing methods, coding standards, code reviews, and source control management; and
• Strong communication skills and a collaborative attitude.