Role: Senior Machine Learning Engineer

Location: Toronto Type: Contract

Role Overview

We are seeking a Senior Machine Learning Engineer (MLE) to build and scale advanced machine learning solutions that drive advertising performance, audience targeting, and forecasting capabilities. This role will focus on time series forecasting, optimization, look-alike audience modeling, ad relevance systems, and click-through rate (CTR) prediction. The ideal candidate has strong experience developing and deploying ML models in production environments and is passionate about solving complex problems at scale.

Key Responsibilities

Design, develop, and deploy machine learning models for: Time series forecasting to predict traffic, demand, campaign performance, and advertising outcomes. CTR (Click-Through Rate) prediction and optimization models. Ad relevance and ranking systems to improve user engagement and campaign effectiveness. Look-alike audience modeling to identify and expand high-value customer segments. Optimization algorithms for bidding, targeting, budget allocation, and campaign performance. Build scalable ML pipelines and production-grade services in cloud environments. Develop feature engineering frameworks leveraging behavioral, transactional, and advertising datasets. Partner with Product, Data Science, and Engineering teams to translate business requirements into ML solutions. Evaluate model performance and continuously improve accuracy, scalability, and operational efficiency. Implement model monitoring, experimentation frameworks, and A/B testing methodologies. Stay current with advancements in machine learning, generative AI, and LLM technologies.

Required Qualifications

Extensive experience building and deploying machine learning models in production environments. Strong expertise in Time Series Forecasting (ARIMA, Prophet, DeepAR, LSTM, Transformer-based forecasting models, etc.), Machine Learning and Statistical Modeling, Optimization techniques and algorithms, Classification, ranking, and recommendation systems, Feature engineering and model evaluation Hands-on experience building large-scale ML systems on GCP, preferably Vertex AI.

Strong programming skills in: Python, Go (Golang), SQL

Experience developing and deploying APIs using FastAPI. General knowledge and practical exposure to Large Language Models (LLMs) and GenAI applications. Experience working with distributed data processing and cloud-native architectures.

Technical Stack

Languages: Python, Go, SQL Cloud: GCP, Vertex AI ML Frameworks: TensorFlow, PyTorch, Scikit-learn, XGBoost APIs: FastAPI Data & Analytics: BigQuery, Spark, Airflow AI/LLMs: OpenAI, Gemini, LangChain (preferred)