Senior Applied Scientist, ML Predictive Maintenance (Asset Intelligence)

Résumé du poste

Design, develop, and optimize machine learning models for fault detection and classification while performing exploratory data analysis on vibration and time-series data. Collaborate with product managers and domain experts to validate hypotheses, define success metrics, and influence architectural decisions.

Détails du poste

MaintainX is a leading mobile-first work execution platform for industrial and frontline teams. More than 13,000 customers, including Duracell, McDonald's, Shell, DHL and Volvo, use MaintainX to cut unplanned downtime and run better operations, across 13.9 million managed assets and 79.5 million completed work orders. In August 2026 MaintainX became part of Autodesk, joining Autodesk Operations Solutions, the organization unifying Autodesk's operations platform alongside Tandem, FlexSim and Fusion Operations. Autodesk's strategy is to converge design, make and operate into one continuous lifecycle: design an asset, build it, run it, then feed what you learn running it back into the next design. Autodesk had design and make. Operate is the phase that tells you what actually happened, and it is ours. As we enter our next phase of growth, we’re investing deeply in AI/ML, LLMs, and Industrial IoT to transform how frontline teams operate—predicting failures before they happen, automating workflows, and embedding intelligence into every asset and procedure. What you’ll do: Design, develop and optimize machine learning models for fault detection and classification end-to-end e.g. data and training modeling choices to evaluation strategies and production constraints. Perform EDA on vibration, OT and time-series data to uncover insights and identify patterns indicative of faults or anomalies. Conduct experiments and evaluation of various algorithms on time-series modeling, signal processing, and statistical methods, to optimize model performance. Partner with PMs in product feature discovery and roadmap prioritization through validating product hypotheses, designing success metrics and quantifying end user impact Collaborate with domain experts to validate findings and ensure alignment with real-world applications. Engage with your community of peers to challenge the status quo, improve our shared ways of working, and influence overall architecture decisions, continuing to foster our culture of Applied Science excellence On-call duties About you: Master’s or Ph.D. in Computer Science, Data Science, Mechanical Engineering, Electrical Engineering, or a related field with a focus on condition monitoring or machine learning applications. 5+ years of proven programming skills using standard ML tools such as Python, PyTorch, Tensorflow etc. Strong foundational knowledge in machine learning, data science, and statistics Familiarity with time-series modeling techniques and feature engineering. Ability to deliver production-grade code that is well-tested, maintainable, and evaluated through rigorous experimentation. An expert level of English, both spoken and written, is required, as the individual will need to lead platform engineering managers across multiple teams, present technical priorities to executive stakeholders, and align with engineering leaders outside Québec on a daily basis. Bonus skills: Hands-on experience developing models for OT and vibration analysis, condition monitoring, and fault detection or classification. Familiarity with signal processing techniques (e.g., Fourier transforms, wavelet analysis) and their application to OT and vibration data. Our mission is to keep the physical world running. Factories, fleets, hospitals and campuses stay up because the people who maintain them have tools worth using. That is what we build. Compensation and benefits. Base pay is one part of the package. Depending on the role, compensation may also include commission, an annual bonus and equity. Benefits differ by country. For roles in the United States, Autodesk’s benefits are described at benefits.autodesk.com. For roles in Canada and other countries, the plan differs on health coverage, retirement and leave, and your recruiter will walk you through it. Belonging. We take pride in a culture where everyone can thrive. More at autodesk.com/company/global-belonging. More on where this is going: Autodesk CEO Andrew Anagnost on building the future of connected operations, and AOS SVP Stephen Hooper on welcoming MaintainX to Autodesk.

Ce que vous ferez

Design, develop, and optimize machine learning models for fault detection and classification while performing exploratory data analysis on vibration and time-series data. Collaborate with product managers and domain experts to validate hypotheses, define success metrics, and influence architectural decisions.

Exigences

Requires a Master’s or Ph.D. in a technical field with a focus on condition monitoring or machine learning. Candidates must have 5+ years of programming experience with standard ML tools and strong foundational knowledge in statistics and time-series modeling.

Avantages

• Equity • Annual bonus • Health coverage • Retirement plan • Leave

Compétences indiquées

• Analyse de données · Souhaitée
• Apprentissage automatique · Souhaitée
• Python · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Machine learning
• Python
• PyTorch
• Tensorflow
• Time-series modeling
• Signal processing
• Fault detection
• Data science
• Statistics
• Feature engineering
• Vibration analysis
• Condition monitoring
• Industrial IoT
• Predictive maintenance
• Data analysis
• Time Series Modeling
• Influencing Skills
• Autodesk
• Influencing Without Authority
• Workflow Automation
• Industrial Internet Of Things (IIoT)
• Artificial Intelligence
• Algorithms
• Electrical Engineering
• Applied Science
• Computer Science
• Condition Monitoring
• Vibrations
• English Language
• Flexsim
• Python (Programming Language)
• Mechanical Engineering
• Machine Learning
• Operations
• Product Family Engineering
• TensorFlow
• Signal Processing
• Statistical Methods
• Time Series
• Autodesk Mechanical Desktop
• Prioritization
• Feature Engineering
• Data Science
• PyTorch (Machine Learning Library)
• Applied Machine Learning

Domaines d’emploi

• Technology
• Engineering
• Software
• Data & Analytics
• Science & Research
• Applied Scientist
• Machine Learning Engineer
• Software Developers
• Computer and Information Research Scientists