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Mlops Engineer Jobs in Quebec (NOW HIRING)

... MLOps principles STAND OUT WITH... * Experience building LLM-powered applications or proof-of-concepts using prompt engineering, RAG (Retrieval-Augmented Generation), fine-tuning approaches

... MLOps principles STAND OUT WITH... * Experience building LLM-powered applications or proof-of-concepts using prompt engineering, RAG (Retrieval-Augmented Generation), fine-tuning approaches

... MLOps principles STAND OUT WITH... * Experience building LLM-powered applications or proof-of-concepts using prompt engineering, RAG (Retrieval-Augmented Generation), fine-tuning approaches

... et MLOps en soutien aux applications d'IA) Mettre en place et maintenir les systèmes de ... DevOps et d'intégration/déploiement continus (CI/CD : GitLab CI, Jenkins, GitHub Actions ou ...

Concevoir, automatiser et maintenir les chaînes d'intégration et de déploiement continus (CI/CD) ainsi que les pratiques DevOps (et MLOps en soutien aux applications d'IA) * Mettre en place et ...

... MLOPS) * Work alongside data scientists and IT experts on a multidisciplinary squad to design ... Develop and maintain application programming interfaces (APIs) and software development kits (SDKs ...

MLOps et systèmes temps réelExpérience avec Google Vertex AI (préféré) ou Amazon SageMaker ... As a Senior ML/DL Developer in the Neuro Squad, you will architect the intelligence behind these ...

$190 - $280/hr

Lead productization of Fidus's engineering expertise into scalable, repeatable AI-augmented ... Manage AI vendor and tool relationships - model providers, MLOps platforms, and data tooling - in ...

New

You have a solid understanding of MLOps practices. * You have experience integrating large language ... You enjoy and are highly proficient in Python programming (knowledge of C++ is considered an asset)

This is an opportunity to run a field engineering team, helping customers understand and implement ... MLops platforms, data platforms and more. We are rapidly expanding the range of open source ...

Showing results 41-60

Mlops Engineer information

Are MLOps engineers in demand?

MLOps engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

What is an MLOps engineer?

An MLOps Engineer is responsible for deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and operations by automating workflows, optimizing infrastructure, and ensuring model reliability. Their role includes CI/CD for ML models, data pipeline management, and performance monitoring. They also work with cloud platforms, containerization, and orchestration tools to scale ML systems efficiently.

What are some common challenges MLOps engineers face in their daily work?

Mlops Engineers often encounter challenges in integrating new machine learning models into existing production systems while ensuring minimal downtime and maintaining data integrity. Managing the scaling and orchestration of models across various cloud or on-prem environments can be complex, requiring close coordination with data scientists and DevOps teams. Staying up to date with rapidly evolving tools and best practices is also essential in this field. Addressing these challenges provides valuable opportunities to innovate and improve both technical processes and team collaboration.

What are the key skills and qualifications needed to thrive as an MLOps engineer, and why are they important?

To thrive as an Mlops Engineer, you need strong skills in software engineering, machine learning pipelines, and cloud infrastructure, often backed by a degree in computer science, engineering, or a related field. Familiarity with tools such as Docker, Kubernetes, TensorFlow, AWS/GCP/Azure, and CI/CD systems is essential, and certifications like AWS Certified Machine Learning or Kubernetes Administrator are often valued. Effective communication, problem-solving, and teamwork are crucial soft skills for collaborating across data science and IT teams. These abilities enable Mlops Engineers to efficiently deploy, manage, and scale machine learning models in dynamic production environments.

What does an MLOps engineer do?

An MLOps engineer is responsible for deploying, managing, and maintaining machine learning models in production environments. They work with tools like Docker, Kubernetes, and cloud platforms to automate workflows, ensure model reliability, and monitor performance. Their role combines software engineering, data science, and DevOps practices to streamline the deployment and lifecycle management of machine learning systems.
What are popular job titles related to Mlops Engineer jobs in Quebec? For Mlops Engineer jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Mlops Engineer jobs in Quebec look for? The top searched job categories for Mlops Engineer jobs in Quebec are:
Infographic showing various Mlops Engineer job openings in Quebec as of August 2026, with employment types broken down into 92% Full Time, 3% Part Time, and 5% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution.

Data Scientist

BRP

Longueuil, QC • On-site

Full-time

Medical, Retirement

This job post has expired today. Applications are no longer accepted.


Job description

Be a part of a fast-paced culture and community in a startup-like environment inside one of the most successful organizations in Québec. We are focused on building a highly talented and ambitious team from the ground up that revolutionizes the way we work around Data & Analytics at BRP. We are a team that has the potential to unlock tremendous value for the organization and you have the unique opportunity to be part of it from the beginning.

Join BRP's central Data & Analytics team (DNA) as a Data Scientist and bring your analytical skills and business insight to our dynamic team. This role is perfect for someone who seeks to blend their understanding of business intelligence with the predictive power of data science to unlock new opportunities for BRP.

YOU’LL HAVE THE OPPORTUNITY TO:

  • Partner with Product Managers, Product Owners, and business stakeholders to surface high-impact opportunities, translating business questions into well-defined analytical and ML problems

  • Design, build, and validate machine learning models and statistical analyses, with clear success metrics tied to outcomes and a strong focus on validity, fairness, and interpretability

  • Plan and execute rigorous A/B tests, experiments, and causal inference studies to validate model performance and measure real business impact

  • Communicate complex findings to non-technical audiences through compelling data storytelling, turning numbers into narratives that drive decisions

  • Stay ahead of rapid developments in foundation models, LLMs, and agentic systems, evaluate their applicability to our context and champion adoption where it creates genuine value

YOU’LL THRIVE IN THIS ROLE IF YOU HAVE THE FOLLOWING SKILLS AND QUALITIES:

Education & Experience

  • MSc (preferred) or BSc in Statistics, Data Science, Computer Science, Mathematics, Engineering, Economics, or equivalent quantitative field

  • 5+ years of hands-on experience applying data science and machine learning to solve real business problems

  • Demonstrated track record of projects where your work drove measurable business outcomes

Technical Skills

  • Strong Python proficiency for data analysis, modeling and deep learning frameworks (PyTorch or TensorFlow)

  • Practical experience with LLM APIs and tools (OpenAI, Anthropic Claude, or similar) for prototyping and implementing AI-powered solutions

  • Solid SQL skills and experience querying data warehouses (Snowflake experience is a plus)

  • Familiarity with at least one end-to-end ML platform (Dataiku, Databricks, Vertex AI or SageMaker) for experimentation and model development

  • Solid grasp of ML fundamentals: model evaluation, cross-validation, hyperparameter tuning, bias-variance tradeoffs, and MLOps principles

STAND OUT WITH…

  • Experience building LLM-powered applications or proof-of-concepts using prompt engineering, RAG (Retrieval-Augmented Generation), fine-tuning approaches

  • Familiarity with AI agent frameworks and orchestration tools (LangGraph, LangChain, CrewAI, or similar) and agent harness

  • Experience with model explainability techniques (SHAP, LIME) and bias/fairness assessment in production contexts

  • Knowledge of the full MLOps lifecycle: model monitoring, drift detection, and retraining strategies

  • Open-source contributions or publications reflecting thought leadership in data science or AI

  • Experience mentoring junior data scientists or leading analytical initiatives

ACKNOWLEDGING THE POWER OF DIVERSITY

BRP is dedicated to nurturing a culture that invites, connects, and propels the ambitions of people of all backgrounds, profiles, beliefs and experiences. Ultimately, the diversity and uniqueness of our people fuel our ingenuity and set the course for the path ahead!

For this reason, we value diversity and we strive to always push each other forward to build an inclusive workplace where every employee feels like they belong, where they can grow and find meaning.

AT BRP, WHEN WE TALK ABOUT BENEFITS, WE GO ALL IN.

Let’s start with a strong foundation - You want it, we have it:

  • Annual bonus based on the company’s financial results

  • Generous paid time away

  • Pension plan

  • Collective saving opportunities

  • Industry leading healthcare fully paid by BRP

What about some feel good perks:

  • Flexible work schedule

  • A summer schedule that varies by department and location

  • Holiday season shutdown

  • Educational resources

  • Discount on BRP products

WELCOME TO BRP

We’re a world leader in recreational vehicles and boats, creating innovative ways to move on snow, water, asphalt, dirt and even in the air. Headquartered in the Canadian town of Valcourt, Quebec, our company is rooted in a spirit of ingenuity and intense customer focus. Today, we operate manufacturing facilities in Canada, the United States, Mexico, Finland, Australia and Austria, with a workforce made up of close to 17,000 spirited people, all driven by the deeply held belief that at work, as with life itself, it’s not about the destination: It’s about the journey.
#LI-Hybrid
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