Machine Learning Software Engineer

Royal Bank of Canada

Toronto, Canada
Building modular software systems in python
Full software development life cycle practices
Ml/genai research and product lifecycle experience
As a Machine Learning Software Engineer, you will own and deliver projects end to end, from data pre-processing to building and scaling ML/GenAI powered solutions and deploying production systems

Job Summary

  • As a Machine Learning Software Engineer, you will own and deliver projects end to end, from data pre-processing to building and scaling ML/GenAI powered solutions and deploying production systems.
  • RBC Borealis is a team that works directly with leading machine learning researchers and designs AI-powered products to support a large enterprise in the financial industry.
  • The role offers a dynamic and flexible working environment with leadership support for professional development and an opportunity to make a lasting impact from local to global scale.

Matching Summary

As a Machine Learning Software Engineer, you will own and deliver projects end to end, from data pre-processing to building and scaling ML/GenAI powered solutions and deploying production systems.

Skills & Requirements

Must-have

  • Building modular software systems in Python
  • Full software development life cycle practices
  • ML/GenAI research and product lifecycle experience
  • Data pre-processing and exploration
  • Deployment and monitoring of production systems

Nice-to-have

  • Building microservices and data pipelines
  • Experience with relational and non-relational databases
  • Front-end development best practices
  • DevOps engineering including CI/CD and containers
  • Collaborative and progressive team environment

Key Requirements

  • Experience in Python or similar language
  • Knowledge of software engineering best practices
  • Experience across ML/GenAI research and product lifecycle
  • Full time employment availability
  • Work authorization in Canada

Work Rights

Not specified

Tailored Resume

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