Job opportunity
Machine Learning & Algorithms Engineer
Lisplogics
About Lisplogics
Lisplogics is a Montreal-based company that builds real-time optimization systems for business operations. We use operations research to help organizations plan and manage their operations as they happen. Our systems run in production and are used daily by our clients.
The role
We are looking for a Machine Learning & Algorithms Engineer with a strong mathematical background. You will design the models and algorithms at the core of our systems: optimization, forecasting and decision models that run on live operational data. You will also work directly with clients, in French, to understand their problems and explain your approach.
What you will do
Translate client operational problems into mathematical models
Design and implement optimization algorithms (linear and mixed-integer programming, heuristics, metaheuristics)
Build machine learning models for forecasting and decision support
Test, benchmark and improve models on real data
Work with our engineering team to deploy models in production
Present results to clients and explain the reasoning behind them
What we are looking for
A degree in mathematics, statistics, operations research, physics, engineering or another quantitative field. A graduate degree is an asset.
Deep quantitative skills: linear algebra, probability, statistics and optimization
Hands‑on experience with machine learning, from model design to validation
Strong programming skills in Python. C++ or Go is an asset.
Ability to explain technical work clearly to non-technical clients
Lives in the Montreal area
Fluent in French
Nice to have
Experience with solvers such as Gurobi, CPLEX or OR-Tools
Experience with real-time or large-scale data
Background in transportation, logistics or operations management
Compensation
Around $140,000 per year, depending on experience.
Work arrangement
The position is remote to start. We may move to a hybrid model in early 2027, details to be confirmed.
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Apply on source site Lisplogics is a Montreal-based company that builds real-time optimization systems for business operations. We use operations research to help organizations plan and manage their operations as they happen. Our systems run in production and are used daily by our clients.
The role
We are looking for a Machine Learning & Algorithms Engineer with a strong mathematical background. You will design the models and algorithms at the core of our systems: optimization, forecasting and decision models that run on live operational data. You will also work directly with clients, in French, to understand their problems and explain your approach.
What you will do
Translate client operational problems into mathematical models
Design and implement optimization algorithms (linear and mixed-integer programming, heuristics, metaheuristics)
Build machine learning models for forecasting and decision support
Test, benchmark and improve models on real data
Work with our engineering team to deploy models in production
Present results to clients and explain the reasoning behind them
What we are looking for
A degree in mathematics, statistics, operations research, physics, engineering or another quantitative field. A graduate degree is an asset.
Deep quantitative skills: linear algebra, probability, statistics and optimization
Hands‑on experience with machine learning, from model design to validation
Strong programming skills in Python. C++ or Go is an asset.
Ability to explain technical work clearly to non-technical clients
Lives in the Montreal area
Fluent in French
Nice to have
Experience with solvers such as Gurobi, CPLEX or OR-Tools
Experience with real-time or large-scale data
Background in transportation, logistics or operations management
Compensation
Around $140,000 per year, depending on experience.
Work arrangement
The position is remote to start. We may move to a hybrid model in early 2027, details to be confirmed.
#J-18808-Ljbffr