Machine Learning Research Engineer at RBC Borealis applying ML technology to complex problems with a focus on generative AI, NLP, and time series analysis.
About the role
- Innovation Engineer exploring AI and emerging technologies to solve business problems. Prototype solutions and drive innovation for operational improvement and product capabilities.
Responsibilities
- Deliver a steady cadence of meaningful proof-of-concept implementations exploring how emerging technologies can address specific product or operational challenges.
- Evaluate emerging technologies in controlled environments to determine whether they are suitable for eventual integration into the core product.
- Identify opportunities that leverage modern technologies (particularly AI) to amplify what we can already do, enabling faster delivery, improved efficiency, and new product possibilities.
- Share prototypes, findings, and techniques with the engineering team to encourage experimentation and adoption of useful technologies, helping catalyze innovation across the organization.
- Provide periodic insight to engineering leadership on emerging technologies and their implications for product capabilities, engineering workflows, and long-term strategy.
Requirements
- Strong hands-on experience applying modern AI technologies such as LLM APIs, RAG, prompt engineering and evaluation, AI workflow orchestration, agent-based frameworks, and AI-assisted automation.
- Comfortable leveraging modern AI platforms such as OpenAI, Anthropic, and Google Gemini to rapidly prototype solutions.
- Comfortable operating as an autonomous builder capable of handling the full lifecycle of a project—from frontend UI for demos to backend logic and basic cloud deployment — without requiring support from existing sprint teams.
- Ability to identify Minimum Viable Value.
- Actively follows emerging technologies and industry trends, identifying meaningful signals while filtering out short-lived hype.
- Demonstrated ability to rapidly experiment with emerging technologies and translate ideas into working prototypes, supported by a portfolio of side projects, experiments, or technical initiatives.
- Ability to explain complex systems to both technical and non-technical audiences — connecting ideas to customer value and operational impact for business stakeholders, while discussing latency, cost, scalability, and data considerations with engineers.
Benefits
- Extended health, dental and vision care
- 20 days vacation
- Flexible work options (office, hybrid or remote)
- Stock options
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