Senior Machine Learning Engineer

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)

Design and deploy machine learning models for time series forecasting, CTR prediction, and audience targeting to improve advertising performance. Build scalable ML pipelines and production-grade services within cloud environments while collaborating with cross-functional teams.

Extensive experience in deploying production ML models with expertise in time series, optimization, and ranking systems. Proficiency in Python, Go, and SQL, with hands-on experience using GCP and Vertex AI.

• SQLPreferred
• GoPreferred
• Machine learningPreferred
• Google CloudPreferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Time Series Forecasting
• Machine Learning
• Optimization Algorithms
• CTR Prediction
• Look-alike Audience Modeling
• GCP
• Vertex AI
• Python
• Go
• SQL
• FastAPI
• Large Language Models
• Generative AI
• TensorFlow
• PyTorch
• BigQuery

• Technology
• Data & Analytics
• Software
• Engineering
• Consulting

Minimum experience

5+ years

Apply by

Sep 4, 2026

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level

Application method

Direct apply is available