Machine Learning Researcher
Role Summary
We're looking for a Machine Learning Quantitative Researcher to design, build, and optimize systems that power advanced machine learning models in a high-performance trading environment. You'll own the full model lifecycle, from research and prototyping through deployment and monitoring, while collaborating with experienced engineers and researchers to deliver scalable, reliable, and efficient solutions. The ideal candidate combines strong software engineering skills, deep machine learning expertise, and a practical approach to performance optimization.
Key Responsibilities
Model Lifecycle Ownership: Research, design, and implement machine learning models; manage deployment, monitoring, and iterative improvements.
System Design & Optimization: Build scalable and performant systems for training and inference; optimize for diverse hardware configurations including GPUs.
Performance Engineering: Profile and tune models and pipelines for speed, accuracy, and resource efficiency.
Software Development: Write clean, modular, and testable code; enforce best practices in architecture, testing, and code reviews.
Infrastructure & MLOps: Develop and maintain tooling for model deployment, validation, and monitoring; integrate with CI/CD pipelines.
Collaboration & Leadership: Partner with cross-functional teams to solve complex technical challenges; lead initiatives and mentor peers.
Documentation & Standards: Maintain clear technical documentation, design records, and operational runbooks.
Core Skills
- Experience: 4+ years building software for machine learning systems in production environments.
- Machine Learning Expertise: Strong understanding of algorithms, probability, statistics, and information theory.
- Programming: Proficiency in Python and experience with GPU programming (CUDA, OpenCL).
- MLOps: Hands-on experience with model deployment, monitoring, and lifecycle management.
- Performance Optimization: Ability to diagnose bottlenecks and optimize across hardware and software layers.
- Collaboration: Excellent communication skills and ability to work effectively in a team setting.
Preferred Qualifications
- Advanced degree in Computer Science, Mathematics, Physics, or related field.
- Familiarity with distributed systems, multi-threaded programming, or hardware/software interaction.
- Experience with CI/CD pipelines and containerized environments (Docker/Kubernetes).
- Exposure to financial markets or trading systems is a plus but not required.
- Education: Bachelor's degree minimum; advanced degree preferred.
Locations:
- Montreal, QC
Please note that this firm is not able to sponsor now or in the future.
FAQs
Congratulations, we understand that taking the time to apply is a big step. When you apply, your details go directly to the consultant who is sourcing talent. Due to demand, we may not get back to all applicants that have applied. However, we always keep your CV and details on file so when we see similar roles or see skillsets that drive growth in organisations, we will always reach out to discuss opportunities.
Yes. Even if this role isn’t a perfect match, applying allows us to understand your expertise and ambitions, ensuring you're on our radar for the right opportunity when it arises.
We also work in several ways, firstly we advertise our roles available on our site, however, often due to confidentiality we may not post all. We also work with clients who are more focused on skills and understanding what is required to future-proof their business.
That's why we recommend registering your CV so you can be considered for roles that have yet to be created.
Yes, we help with CV and interview preparation. From customised support on how to optimise your CV to interview preparation and compensation negotiations, we advocate for you throughout your next career move.