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MaintainX is seeking a Senior Applied Machine Learning Engineer to lead technical direction and architecture for Predictive Maintenance and Asset Intelligence initiatives. The company is the world's leading AI-powered maintenance and asset management platform serving 14,000+ customers including Duracell, Shell, Cintas, and Brenntag. Recently raised $150M in Series D funding (total $254M) and valued at $2.5B, MaintainX is investing deeply in AI/ML, LLMs, and Industrial IoT.
In this role, you will lead technical direction for predictive maintenance, anomaly detection, and LLM-powered intelligence across MaintainX products. You'll architect end-to-end ML systems from data ingestion and feature development through model training, deployment, and monitoring. A key responsibility is mentoring a growing team of ML and data developers, instilling best practices for experimentation, evaluation, and model lifecycle management.
You'll partner with product and software development leaders to align the AI roadmap with customer needs and business goals. You'll design reliable data and feedback loops connecting customer telemetry and operator feedback to model retraining. Performance optimization through techniques like quantization, distillation, and scalable inference serving will be part of your scope. You'll work with LLM frameworks (LangChain, LlamaIndex, Hugging Face) to build reasoning systems and agentic workflows for asset and work intelligence, ensuring ML infrastructure meets production standards for latency, reliability, explainability, and security.
Required: 7+ years in Machine Learning, Data Science, or Applied AI; expertise in Python, PyTorch, TensorFlow, and cloud ML stacks (AWS, Databricks); proven experience deploying production ML systems at scale; strong background in LLMs, time-series modeling, and anomaly detection; demonstrated ability to lead architectural decisions and mentor developers; knowledge of MLOps tooling (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker). Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field preferred.
Bonus: OCR experience, time-series modeling for predictive maintenance, Industrial IoT systems knowledge, reinforcement learning or agentic architectures, open-source ML contributions.
