Own ML/Applied AI for product: transform telemetry into detections, risk scores, and baselines to
Shape architecture decisions: telemetry pipeline, model deployment, versioning, and A/B testing of

🎯 Requirements

5+ years ML engineering; 2+ years deploying production ML systems
Strong fundamentals: gradient-boosted trees, regression, classification, feature engineering
Experience with anomaly detection or time-series modelling
Hands-on use of LLMs for applied tasks: function calling, retrieval-augmented generation
Python and ML stack: scikit-learn, PyTorch or TensorFlow, pandas
Experience with large-scale telemetry data: ClickHouse, BigQuery, Snowflake, Spark

🎁 Benefits

Office locations: Vancouver, Canada; hybrid work model
Competitive compensation, health, vision, dental benefits
Opportunities to publish research and present at conferences

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