Senior Machine Learning Engineer

Rate

CAD$90-100/hr INC

What You'll Do

• Architect and implement advanced deep learning models for multimodal recommendation systems, processing diverse data types including text, images, user behavior, item features, offer data, and contextual signals.
• Lead the development and optimization of generative AI applications for personalized product discovery, search enhancement, and customer engagement.
• Expert in leveraging cutting‑edge GenAI techniques, prompt engineering, transformer architectures, and own end‑to‑end development of scalable AI/ML pipelines.
• Design, build, and maintain highly scalable, robust, and efficient cloud infrastructure using Google Cloud Platform (GCP) services, including Vertex AI, BigTable, BigQuery, AlloyDB, and Cloud Composer.
• Develop automation and orchestration of ML pipelines, integrating data ingestion, feature engineering, training, and deployment processes.
• Collaborate with cross‑functional teams to understand their needs and build solutions that improve platform usability, scalability, and the overall development experience.
• Optimize data processing pipelines and cloud resources to ensure low‑latency, cost‑effective operation.
• Implement monitoring, alerting, and failover strategies to ensure platform reliability.
• Stay updated with industry trends and best practices in cloud engineering, data engineering, and machine learning.

Required Qualifications

• Master's or PhD in Computer Science, Machine Learning, or related field.
• 8+ years of experience in machine learning engineering, with a focus on recommendation systems or personalization.
• Strong expertise in deep learning frameworks (PyTorch or TensorFlow) and building production‑grade ML systems.
• Proven experience with GCP services and ML infrastructure at scale.
• Proficient in Python, SQL, and cloud‑native development.
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Track record of deploying ML models to production at scale.

Preferred Qualifications

• Experience with multimodal deep learning architectures and generative AI models.
• Knowledge of modern recommendation system architectures (transformers, neural collaborative filtering).
• Expertise in building real‑time inference systems.
• Experience with distributed computing frameworks (Spark) and big data processing.
• Familiarity with Apache Airflow (Cloud Composer) and CI/CD pipelines.