Machine Learning Engineer, Recommendations

Senior-level Application Release Engineer to enhance software delivery and release management using automation-first approaches. Focuses on scalability, reliability, and efficiency in a financial services environment.

Develop and maintain machine learning models and systems to detect fraudulent transactions and behavior, build scalable feature pipelines, and optimize model performance using MLOps best practices.

Builds ML models and systems for search ranking, relevance, and LLM-driven features. Owns A/B testing and experimentation frameworks for production systems.

Seeking a Senior Machine Learning Engineer to design, build, and operate data and ML infrastructure for AI at scale on the City of Toronto's AWS-based Enterprise Data Platform. Focus is on engineering foundations and deployment frameworks.

Seeking a Senior Machine Learning Engineer to design, build, and deploy scalable ML solutions in cloud/on-premise environments. Requires Python, Snowflake, AWS, and Linux.

Develops and deploys ML models and pipelines at scale, working at the intersection of blockchain and AI.

Develop and deploy machine learning models for renewable energy forecasting and digital twin platforms. Requires Python and deep learning framework proficiency.

Develops and implements machine learning models for character animation generation, working with large datasets, optimizing, and deploying models within Unreal Engine.

This role involves designing and implementing multi-modal ML models, fine-tuning LLMs, and creating real-time ML pipelines to optimize operations.