Senior Machine Learning Researcher

Royal Bank of CanadaMontreal, QC
Onsite

About The Position

RBC Borealis is looking for an enthusiastic Senior Machine Learning Researcher who's excited by the opportunity of being at the forefront of machine learning technology and working on extremely challenging problems in the financial services industry. As a Senior Machine Learning Researcher, you'll be part of a collaborative team delivering AI projects end to end, covering everything from scoping and defining the AI problem, to data pre-processing and exploration, to prototyping novel algorithmic solutions, to software implementations of machine learning-based products. At RBC Borealis you'll be joining a team that works directly with leading researchers in machine learning; and you'll have access to rich and massive datasets and to the computational resources that support cutting-edge machine learning R&D.

Requirements

  • A Ph.D. degree in Computer Science or a related technical field.
  • At least 2 years of experience as a machine learning researcher or engineer in a product-centric environment or equivalent experience.
  • Expertise in machine learning, with experience with large language models and natural language processing being a plus.
  • Experience delivering high-impact machine learning products.
  • Experience mentoring junior researchers and engineers.
  • Involvement across the research and development lifecycle, from prototyping to production, engaging with stakeholders to develop solutions that meet business needs.
  • The ability to formulate and drive a research project independently.
  • Exceptional communication skills.
  • A history of high-quality academic publications (e.g., NeurIPS, ACL, EMNLP, CVPR, ICLR, ICML etc.).
  • Collaboration
  • Communication
  • Computer Programming
  • Data Science
  • Large Language Models (LLMs)
  • Machine Learning (ML)

Nice To Haves

  • Experience with large language models and natural language processing being a plus.

Responsibilities

  • Apply deep technical expertise and scientific rigour to AI projects, working within and across teams.
  • Develop innovative machine learning approaches and novel intellectual property.
  • Iteratively refine and deliver machine learning concepts from proof of concept through to product delivery.
  • Contribute to defining our research vision, publish papers, and communicate internally and externally around machine learning research.
  • Work closely with team members including other researchers, engineers, and interns to advance AI research and solutioning.
  • Designs and implements cutting edge machine learning methodologies and algorithms to solve complex, high impact problems, ensuring alignment with organizational goals and industry benchmarks.
  • Leads the development and deployment of scalable AI platforms and tools, providing strategic guidance and technical expertise to cross functional teams and stakeholders.
  • Authors and presents peer reviewed publications, represents the organization at international conferences, and collaborates with the scientific community to establish the organization as a leader in AI research.
  • Mentors and provides technical leadership to junior researchers, disseminating knowledge, reviewing research outputs, and fostering innovation to enhance organizational capabilities in machine learning.
  • Leads complex machine learning research initiatives, solving abstract problems and delivering impactful solutions using advanced technical and business expertise.
  • Oversees decision making for highly complex issues with significant financial or operational impact, providing clear direction and actionable recommendations to management on key organizational priorities.
  • Develops and implements innovative solutions to address highly complex machine learning research related problems ensuring alignment with organizational goals.
  • Cultivates and maintains high impact relationships across multiple areas to provide strategic insights and delivering measurable value as a trusted advisor.

Benefits

  • bonuses
  • flexible benefits
  • competitive compensation
  • commissions
  • stock options where applicable
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