Senior Applied Machine Learning Developer (Asset Intelligence)
- United States
- Senior Level
- 7+ years
- Master's degree
- Posted
Skills
Required
- Machine Learning / Data Science / Applied AI
- ML
- predictive maintenance
- time-series modeling
- detection
- Python
- PyTorch
- TensorFlow
- cloud
- AWS
- Databricks
- lead architectural decisions
- mentor developers
- Docker
- Kubernetes
Preferred
- OCR
- Industrial IoT systems
- sensors
- telemetry
- edge computing
- open-source
- ML frameworks
- data ingestion
- feature development
Join MaintainX as a Senior Applied Machine Learning Developer, where you'll lead the technical direction and architecture of our Predictive Maintenance and Asset Intelligence initiatives. You'll combine your deep ML expertise with strong software development and leadership skills, mentoring developers, scaling systems, and driving the roadmap for AI-enabled maintenance intelligence across thousands of industrial sites. This role is at the intersection of ML architecture, IoT data systems, and product impact, shaping the foundation for MaintainX’s predictive and generative AI strategy.
Lead the technical direction and architecture of Predictive Maintenance and Asset Intelligence initiatives, combining deep ML expertise with strong software development skills.
Responsibilities
- Architect end-to-end ML systems, from data ingestion and feature development to model training, deployment, and monitoring, ensuring ML infrastructure meets production standards.
- Mentor a growing team of ML and data developers, instilling best practices for experimentation, evaluation, and model lifecycle management.
Requirements
- 7+ years of experience in Machine Learning, Data Science, or Applied AI
- Proven experience deploying production ML systems—not just prototypes—at scale
- Expertise in Python, and strong familiarity with PyTorch, TensorFlow, and cloud ML stacks (AWS, Databricks, or similar)
- Demonstrated ability to lead architectural decisions, mentor developers, and collaborate across product, data, and platform teams
- Strong background in LLMs, time-series modeling, and anomaly detection for real-world data
- Knowledge of MLOps tooling (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker)
- Background in time-series modeling for predictive maintenance and anomaly detection
- Experience applying reinforcement learning or agentic architectures for decision-making and control systems
Preferred
- Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field preferred
- Experience with OCR for extracting structured data from documents
- Familiarity with Industrial IoT systems (sensors, telemetry, edge computing)
- Contributions to open-source ML frameworks or research in reliability, explainability, or digital twins
Pay
USD 131,400 - 236,000
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