ML Engineer

📋 Description

• 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