[Hiring] Senior Machine Learning Engineer @Insight

Role Description

As a Senior Machine Learning Engineer, you will lead the modeling work on enterprise engagements where ML models are often integrated directly into multi-agent systems. We will count on you to span data exploration, feature engineering, model development across multiple business segments, integration into agent response loops, and operating the full MLOps lifecycle on Gemini Enterprise Agent Platform (GEAP). Along the way, you will get to:

• Build anomaly detection and regression models.
• Develop end-to-end pipelines that check data quality, engineer features, train, tune and evaluate models, and perform either batch or online inference.
• Migrate legacy ML workloads onto GEAP (formerly known as Vertex AI).
• Translate existing models from platforms such as Dataiku or SageMaker into KFP-based pipeline templates on GEAP.
• Own drift detection and retraining.
• Implement input and output distribution shift detection and accuracy regression checks.
• Define per-model thresholds and retraining cadence, set up alerting and logic for decisions on when to re-train a model.
• Ensure retraining deploys through the standard CD pipeline with canary, approval gate, and automated rollback.
• Ensure every model is registered in GEAP Model Registry with model cards capturing ownership, lineage, evaluation results, and lifecycle state.

This opportunity is not just about what you do today but also about where you can go tomorrow. When you bring your hunger, heart, and harmony to Insight, your potential will be met with continuous opportunities to upskill, earn promotions, and elevate your career.

Qualifications

• 5+ years applied ML engineering, with at least 2 years productionizing models at scale.
• Deep GEAP experience: Model Registry, Pipelines (KFP), Experiments, Feature Store, and Workbench.
• Strong regression and anomaly detection skills: Gradient boosting (XGBoost / LightGBM / CatBoost), classical statistical anomaly methods (IQR, isolation forests, robust z-scores), and at least one deep approach (autoencoders, normalizing flows).
• Production Python: Type-annotated, tested, packaged. Comfortable with pandas, NumPy, scikit-learn, and the GEAP SDK.
• Familiar with KFP DSL for pipeline authoring.

Requirements

• The base salary range for this position is typically $140,000 CAD to $160,000 CAD with additional bonus and benefits available.
• Compensation decisions are dependent on the facts and circumstances of each case, including experience and location.
• We will also consider candidates outside of this range as necessary.

Benefits

• We’re legendary for taking care of you, your family and to help you engage with your local community.
• Core values of Hunger, Heart, and Harmony guide everything we do.