Machine Learning Researcher

1 week ago

Montreal, Quebec, Canada Selby Jennings Full time

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.

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