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Senior Machine Learning Engineer Jobs in Montreal, QC

We are seeking a Senior Machine Learning (ML) Research Scientist to join our team working on a ... Benchmark and optimize model performance and efficiency along with ML engineers to ensure the ...

We're looking for a highly motivated Applied Machine Learning Scientist II to join our AI2 team. In ... Experience with structured and unstructured data, feature engineering, and model interpretability ...

... As a Senior ML Developer on the team, you will be responsible for leading/contributing to the ... Design and implement Machine Learning capabilities that improve Autodesk's RAG platforms * Perform ...

We are seeking a senior distributed machine learning (ML) research developer to join our team working on a novel AI safety agenda. In this role, you will work closely with ML research scientists to ...

The Role We're hiring our Senior Data Engineer (Data / ML Platform) to stand up data engineering as ... Machine Learning Platform Exposure: Experience supporting machine learning workflows, feature ...

What you will be doing Artefact is looking for a Senior AI & Data Scientist: a scientist who owns ... Cloud certifications, especially Google Cloud Professional Machine Learning Engineer. * Why Join Us ...

Join our Machine Learning Platform team and help bring models, including Large Language Models ... As a Backend Developer, you will: * Contribute to the development lifecycle, including coding ...

Join our Machine Learning Platform team and help bring models, including Large Language Models ... As a Backend Developer, you will: * Contribute to the development lifecycle, including coding ...

Work with our machine learning engineers to put cutting edge deep learning algorithms in production. * Develop tools and contribute to open source wherever possible. * Adopt problem solving as a way ...

Showing results 21-40

Senior Machine Learning Engineer information

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What are the key skills and qualifications needed to thrive as a senior machine learning engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Montreal, QC?

The most popular types of Machine Learning Engineer jobs in Montreal, QC are:

What are popular job titles related to Senior Machine Learning Engineer jobs in Montreal, QC?

For Senior Machine Learning Engineer jobs in Montreal, QC, the most frequently searched job titles are:

What job categories do people searching Senior Machine Learning Engineer jobs in Montreal, QC look for?

The top searched job categories for Senior Machine Learning Engineer jobs in Montreal, QC are:

What cities near Montreal, QC are hiring for Senior Machine Learning Engineer jobs?

Cities near Montreal, QC with the most Senior Machine Learning Engineer job openings:

Infographic showing various Senior Machine Learning Engineer job openings in Montreal, QC as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 20% Part Time, and 1% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Senior ML Research Scientist

LawZero

Montreal, QC โ€ข On-site

Full-time

Medical, Retirement, PTO

Re-posted 4 days ago


Job description

We are seeking a Senior Machine Learning (ML) Research Scientist to join our team working on a novel AI safety agenda. In this role, you will design and implement innovative ML models aimed at solving advanced AI safety problems.

Key responsibilities

  • Propose, design, and implement novel ML models tailored to solve complex AI safety problems.
  • Collaborate with mathematicians and other specialized research scientists to integrate theoretical advancements into practical ML algorithms and models.
  • Adapt and fine-tune existing frontier models to enhance their applicability to specific settings.
  • Design and implement experimental protocols and evaluation frameworks to validate hypotheses and ensure robust and reproducible results, including at the scale and complexity of frontier models.
  • Analyze and interpret experimental data in order to steer future research questions and objectives.
  • Benchmark and optimize model performance and efficiency along with ML engineers to ensure the optimal usage of computing resources over the course of long experiments.
  • Communicate findings and synchronize work with other researchers and engineers.

Required skills and qualifications

  • Advanced degree in a relevant field (e.g., Computer Science, Mathematics). A PhD is preferred but not required if the candidate demonstrates exceptional abilities.
  • 5+ years of experience in deep learning research projects, in particular with frontier models.
  • Proven experience in the training, adaptation, and/or fine-tuning of frontier models across a variety of complex scenarios that involve, for example, transfer learning, domain adaptation, or meta learning.
  • Expertise in the integration and use of ML libraries such as PyTorch, TensorFlow, or JAX for the development, training, and evaluation of ML models, ideally in distributed computing environments.
  • Strong experience in Python software development, in the use of version control, collaboration tools, and experiment management and tracking tools.
  • Strong communication skills, both written and verbal, with the ability to exchange ideas with researchers across different disciplines.
  • Ability to work collaboratively in a team environment while also being self-motivated and independent.
Preferred skills and qualifications
  • Experience analyzing the behavior of frontier models in safety-critical contexts.
  • Experience in the design and development of model alignment strategies or benchmarks.
  • Experience with natural language processing or probabilistic graphical models.
  • A track record of contributing to high-quality research projects in deep learning.

What we offer

  • The opportunity to contribute to a unique mission with a major impact.
  • Comprehensive health benefits.
  • A minimum of 20 days vacation per year upon start.
  • A minimum retirement savings employer contribution of 4%.
  • Generous flexible benefits designed to contribute to your well-being.
  • A team of passionate experts in their field.
  • A collaborative and inclusive work environment with offices in the heart of Little Italy, in the trendy Mile-Ex district, close to public transportation.