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
- AI/ML Innovation Engineer at EWSGroup designing and operationalizing AI capabilities in the product ecosystem. Involves hands-on work with machine learning models and data pipelines.
Responsibilities
- Research, design, and build AI/ML prototypes that enhance product functionality or internal efficiency
- Experiment with large language models (LLMs), vector databases, and RAG pipelines
- Develop and test algorithms for prediction, optimization, and intelligent automation
- Evaluate and integrate APIs and SDKs from Azure AI, OpenAI, and other emerging AI platforms
- Work with product teams to define viable use cases and success metrics for AI features
- Partner with DevOps and data engineering teams to scale prototypes into production-ready components
- Document and share technical approaches for reusability across projects
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, or related field
- 4–8+ years of experience in software engineering or ML development (Python preferred)
- Proficiency with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
- Experience designing, deploying, and maintaining AI systems end-to-end, including RAG pipelines, fine-tuned LLMs, and cloud deployment on AWS or Azure (Azure OpenAI, Amazon Bedrock, SageMaker JumpStart)
- Familiarity with prompt engineering, embeddings, and vector search
- Strong analytical and problem-solving skills with an experimental mindset
- Excellent communication and collaboration skills across technical and business domains.
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