Role Overview
MaintainX is hiring a remote Senior Applied Machine Learning Engineer in Canada to guide the technical direction and architecture of Predictive Maintenance and Asset Intelligence initiatives. This full-time position is ideal for an experienced AI professional looking to shape the future of industrial operations and generative intelligence.
Key Responsibilities
Spearhead the technical strategy for anomaly detection, predictive maintenance, and LLM-powered intelligence across product offerings.
Build and maintain end-to-end machine learning systems spanning data ingestion, feature engineering, model training, deployment, and monitoring.
Guide and mentor a growing team of data and machine learning developers by promoting best practices in evaluation, experimentation, and lifecycle management.
Collaborate closely with product management and software engineering leaders to align the artificial intelligence roadmap with company goals.
Create robust feedback and data loops that integrate operator feedback and telemetry to facilitate continuous model retraining.
Optimize performance through scalable inference serving, quantization, and model distillation.
Utilize large language model frameworks such as LangChain, LlamaIndex, and Hugging Face to develop reasoning systems and agentic workflows.
Guarantee that machine learning infrastructure satisfies strict production standards for security, explainability, latency, and reliability.
Requirements
Seven or more years of professional experience in Applied Artificial Intelligence, Data Science, or Machine Learning.
Proficiency in Python alongside working knowledge of TensorFlow, PyTorch, and cloud machine learning stacks like AWS and Databricks.
Demonstrated history of successfully deploying production-scale machine learning systems rather than isolated prototypes.
Expertise in time-series modeling, large language models, and anomaly detection utilizing real-world data sources.
Proven capability to drive architectural decisions, mentor peers, and partner with cross-functional teams.
Familiarity with modern MLOps tools such as Kubernetes, Docker, MLflow, Weights & Biases, and SageMaker.
Preferred qualifications include an advanced degree (Master of Science or PhD) in Machine Learning, Computer Science, or a related discipline.
Nice to Have
Practical experience utilizing OCR to extract structured information from documents.
Background focused on time-series modeling for predictive maintenance and anomaly detection.
Familiarity with Industrial IoT architectures, including sensors, telemetry, and edge computing environments.
Experience applying reinforcement learning or agentic frameworks for control systems and decision-making.
Prior contributions to open-source machine learning projects or research centered on digital twins, explainability, or reliability.
Skills and Tools
Programming and Frameworks: Python, PyTorch, TensorFlow, LangChain, LlamaIndex, Hugging Face
Infrastructure and Operations: AWS, Kubernetes, Docker, MLOps, MLflow, Weights & Biases, SageMaker, Databricks
Core Competencies: Machine Learning, Artificial Intelligence, LLMs, Predictive Maintenance, Anomaly Detection, Time-Series Modeling
Salary and Benefits
Base compensation ranges from $123,000 to $180,000 CAD per year.
Total compensation package may include an annual bonus, commission, and equity depending on the position.
Comprehensive benefits tailored to Canada covering health, retirement, and leave options, with details provided by the recruiter.
About the Company
MaintainX provides a mobile-first work execution platform utilized by frontline and industrial teams to reduce unplanned downtime across millions of managed assets. Major global brands rely on the platform to streamline operations, and the company became part of Autodesk in August 2026. Autodesk integrates design, manufacturing, and operations into a single continuous lifecycle to transform how the physical world runs.
How to Apply
Interested candidates should visit the official company careers page to submit an application for this remote position.
