Scientifique appliqué principal, maintenance prédictive en apprentissage automatique (intelligence des actifs)
MaintainX17 days ago
Responsibilities
- Design, develop, and optimize machine learning models for end-to-end defect detection and classification.
- Conduct exploratory data analyses on vibration data and time series to derive insights.
- Experiment and evaluate different algorithms for time series modeling and signal processing.
- Collaborate with product managers for feature discovery and roadmap prioritization.
- Work closely with domain experts to validate results in real-world contexts.
- Participate in the internal peer community to improve work methods and influence architecture decisions.
- Engage in on-call rotations.
Requirements
- Master's or PhD in computer science, data science, mechanical engineering, electrical engineering, or a related field with a focus on condition monitoring or machine learning.
- Over 5 years of demonstrated programming experience with standard ML tools like Python, PyTorch, TensorFlow.
- Strong foundational knowledge in machine learning, data science, and statistics.
- Good understanding of time series modeling techniques and feature engineering.
- Ability to deliver production-ready, well-tested, maintainable code validated by rigorous experimentation.
Benefits
- Competitive salary and significant equity opportunities.
- Health, dental, and vision coverage.
- 401(k) / RRSP enrollment program.
- Flexible leave policy.