Machine Learning Specialist

At VibroSystM, our mission goes beyond simple monitoring: we protect critical and strategic infrastructure in the energy and mining sectors. We are engaged in a major transformation, moving from high-precision monitoring to proactive, AI-driven decision support. This transition enables our customers to anticipate failures, prevent breakdowns, and optimize their operations to maximize the lifespan of their equipment. We are looking for a passionate Machine Learning Specialist to strengthen our R&D team. Working closely with our specialized physics/engineering experts, your role will be to evolve our AI models from validated prototypes to robust, production-deployed cloud solutions. This is a highly strategic position. Going far beyond simply adjusting hyperparameters, you will define the architecture of the cloud deployment pipeline, ensuring the scalability of our models across hundreds of industrial assets worldwide.

The Ideal Candidate

• Scientific Ownership: Take ownership of existing models and algorithms. Analyze, debug, and improve existing mathematical logic documentation and implementation;

• Builder's Mindset: You have a strong grasp of model mathematics but prioritize reliable production deployment, essential in an industrial context;

• Product-Oriented: You optimize not only for accuracy but also for latency, cost, and robustness;

• Technical Stack: Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, or Scikit-Learn);

• Time Series Expertise: In-depth expertise in time series analysis (LSTMs, 1D CNNs, Autoencoders) applied to physical signals is critical;

• Engineering First: Experience with software engineering best practices: version control (Git), API development (gRPC, REST), and containerization (Docker/Kubernetes);

• Cloud Knowledge: Experience deploying ML solutions in a cloud environment (ideally GCP) is a major asset;

• Domain Sensitivity: You are comfortable working with data representing physical objects (rotors, stators, vibrations) and value domain expertise.

Why?

By joining the Research & Development team, you will become part of the VibroSystM family. You will work alongside respectful, passionate people who are proud to be part of a globally recognized Quebec company. Here are some of the benefits.

• Integration, training and skills development;

• Group insurance paid by the employer:

  • Medication

  • Dental

  • Sight

  • Health care

  • Life

• Annual bonus;

• Sick/personal leave;

• Registered retirement savings plan with employer contribution;

• Involvement and participation;

• Teamwork and spirit;

• Innovative, patented, and unique technology;

• Flexible work schedule;

• Google Workspace collaboration tool;

• Daily team meetings for team participation in all development projects;

• Decentralized team: Work from home with the stability of a head office based in Longueuil;

• Direct impact: Your code will directly influence critical asset maintenance decisions made by our clients worldwide;

• Autonomy & Ownership: You will step into a key role with immediate impact, taking full ownership of the Data Science roadmap and execution, backed by comprehensive documentation and a supportive engineering team.

Your contribution

We are looking for a Machine Learning Specialist to join our R&D team. You will work closely with our Data Scientist and our physics/engineering experts to take our AI models from the stage of "prototypes validated" to cloud computing solutions deployed in production. This is a high-impact role. You won't just be making adjustments to hyperparameters ; you will define the architecture of the pipeline that deploys our models in the Cloud, ensuring their scalability across hundreds of industrial devices.

Tasks & Responsibilities

• MLOps Pipeline: Define the architecture and build the pipeline to deploy machine learning models on Google Cloud Platform (GCP). Manage the complete lifecycle: from training on historical data to inference in production;

• Model development: Design and train new models using supervised, unsupervised, and semi-supervised learning techniques. You will work to expand our current asset monitoring and diagnostic capabilities;

• Hybrid AI & Collaboration: Work closely with our in-house physics and engineering experts to validate model results against real-world physical phenomena. You will ensure that our AI models complement and coexist with our existing expert rules and algorithms;

• Data Engineering Collaboration: Collaborate with software teams to define data requirements for the Cloud API, ensuring high-quality data ingestion for model training;

• Simulation & Robustness: Explore the use of data simulators to inject noise and edge cases, to ensure that our algorithms remain valid in complex and real-world industrial environments;

• Lifecycle management: Implement MLOps best practices to monitor the performance of models in production, manage retraining cycles and datasets.

Your knowledge and experience

• Bachelor's degree in computer science, software engineering or applied mathematics;

• 3 years and more of experience in machine learning engineering (ML Engineer) or data science. Requires at least one proven experience, covering the entire cycle, from prototype to production;

• Bilingualism (French and English) both orally and in writing (communications outside Quebec);

• Good understanding of continuous integration and continuous deployment (CI/CD) practices;

• Relevant experience with Agile methodologies and collaborative development tools such as Jira, GitHub and Google Workspace;

• Excellent rigor and ability to synthesize information;

• Pragmatic and results-oriented;

• Autonomy in the execution of tasks;

• Excellent communication skills and good team spirit.

Assets