Distributed Systems/Ml Engineer - Montreal - Up To $175,000 Cad + Benefits

The Role:Distributed Systems / ML Engineer
The Client:Elite Rapidly Scaling Quantitative Trading Start-Up
Compensation:Up to $175,000 CAD + Equity + Bonuses
Location:Montreal (Hybrid)
The OpportunityWe're working with a seriously exciting fintech startup building technology at the intersection of finance, data and machine learning.
You'll be designing, building and owning critical systems from the ground up, tackling complex distributed computing and algorithmic challenges. The team is small, highly technical and incredibly ambitious, with a culture built around ownership, autonomy and fast-paced decision making.
What You'll Be Doing
Design, build and scale highly distributed systems processing enormous volumes of data with high throughput, low latency and exceptional reliability.
Develop sophisticated algorithms, mathematical models and ML systems to solve complex, data-intensive problems.
Own critical data and ML infrastructure, from ingestion and processing through to deployment and monitoring.
Build scalable data pipelines and real-time processing systems.
Test, benchmark and optimise models and algorithms using real-world data.
Work closely with engineers and data scientists to take models from experimentation into production.
Take genuine end-to-end ownership, from technical design through to implementation and optimisation.
Who You Are:
Strong Computer Scientist with a proven track record ( 2–7+ years ) solving complex problems.
Strong programming experience in Rust, C++, Python or Golang.
Degree in Computer Science, Mathematics, Engineering, Physics or another quantitative field.
Strong mathematical and computational background, including linear algebra, probability, statistics or optimisation.
Experience with algorithms, machine learning or mathematical modelling.
Deep understanding of distributed systems, system design, scalability and performance optimisation.
Experience working with large-scale data or computationally intensive systems.
Personality! Proactive, intellectually curious and someone who thrives in a high-ownership, fast-paced environment.
Nice to Have:
Experience with MLOps, ML infrastructure or production model deployment.
Exposure to distributed computing, streaming or data processing frameworks.
Experience with optimisation algorithms or statistical modelling.
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