Senior Applied Machine Learning Engineer, Asset Intelligence
Job Description:
- Lead technical direction for predictive maintenance, anomaly detection, and LLM-powered intelligence across MaintainX products.
- Architect end-to-end ML systems—from data ingestion and feature engineering to model training, deployment, and monitoring.
- Mentor a growing team of ML and data engineers, instilling best practices for experimentation, evaluation, and model lifecycle management.
- Partner with product and engineering leaders to align AI roadmap with customer needs and business goals.
- Design reliable data and feedback loops that connect customer telemetry and operator feedback to model retraining.
- Drive performance optimization through techniques like quantization, distillation, and scalable inference serving.
- Work with LLM frameworks (LangChain, LlamaIndex, Hugging Face) to build reasoning systems and agentic workflows for asset and work intelligence.
- Ensure ML infrastructure meets production standards for latency, reliability, explainability, and security.
Requirements:
- 7+ years of experience in Machine Learning, Data Science, or Applied AI.
- Expertise in Python, and strong familiarity with PyTorch, TensorFlow, and cloud ML stacks (AWS, Databricks, or similar).
- Proven experience deploying production ML systems—not just prototypes—at scale.
- Strong background in LLMs, time-series modeling, and anomaly detection for real-world data.
- Demonstrated ability to lead architectural decisions, mentor engineers, and collaborate across product, data, and platform teams.
- Knowledge of MLOps tooling (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker).
- Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field preferred.
Benefits:
- Competitive salary and meaningful equity opportunities.
- Healthcare, dental, and vision coverage.
- 401(k) / RRSP enrollment program.
- Take what you need PTO.
- A high impact Culture:
- You’ll work with Smart, Humble Optimists across the globe.
- Meritocratic environment where ideas and outcomes are publicly celebrated.
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