
Senior Applied Scientist, ML Predictive Maintenance (Asset Intelligence)
Required skills
- Machine Learning
- Python
- PyTorch
- Tensorflow
- time-series modeling
- fault detection
- data science
- statistics
- experimentation
- ML Predictive Maintenance
Nice to have
- Signal Processing
- Fourier transforms
- wavelet analysis
- OT
- vibration analysis
- condition monitoring
Role summary
MaintainX, now part of Autodesk, is seeking a Senior Applied Scientist specializing in ML Predictive Maintenance for its Asset Intelligence team. This role involves designing, developing, and optimizing end-to-end machine learning models for fault detection and classification using time-series, OT, and vibration data. The scientist will conduct experiments, evaluate algorithms, and collaborate with product managers and domain experts to drive product innovation. A Master's or Ph.D. in a relevant field and 5+ years of programming experience with ML tools like Python, PyTorch, and TensorFlow are required. Familiarity with time-series modeling, signal processing, and delivering production-grade code is essential. Bonus skills include hands-on experience with OT/vibration analysis and condition monitoring.
MaintainX is a leading mobile-first work execution platform for industrial and frontline teams. More than 15,000 customers, including McDonalds, Michaels, Cintas, Redimix, and U.S. LBM, use MaintainX to cut unplanned downtime and run better operations, across 16 million managed assets and 92 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.
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