Rbc

SeniorAIEngineer

Toronto, Ontario, Canada FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior AI Engineer at Rbc. Skills: Machine Learning, AI, model development, model deployment, Python, Cloud Platforms, MLOps. Develop and Optimize Machine Learning Models. Ensure Scalable Model Deployment”

What You'll Achieve.

drive business growth and improvement; delivering high-quality solutions that meet business needs; seamless deployment of models into production; scalability; reliability; minimal downtime; efficient testing, versioning, and deployment of new features or updates; meet Service and Operational Level Agreements; build products that can be maintain with least incidents

Industry & Context.

Problems you'll solve

Group Problem Solving

Eligibility Requirements

Ready to provide after hour support on need basis

What They're Looking For.

Must Have

programming skills in languages such as Python, java, or C++, Experience with cloud platforms (AWS, GCP, and Azure), MLOps tools, 2 + years of hands-on experience in model development and optimization, knowledge of advance ML techniques, Hands-on experience with frameworks like Hugging Face Transformers, LangChain, or OpenAI APIs, understand of NLP tasks such as entity recognition, summarization, text classification, Skills in evaluating LLM performance using metrics, proficiency in creating, maintaining, and troubleshooting DAGs for scheduling and orchestrating ML workflows, Experience in integrating Airflow with cloud data storage and ETL pipelines, Experience with data pipelines using tools like Apache Spark or Pandas for handling structured and unstructured data, understand the tools like AWS SageMaker for building, training, and deploying ML models, Hands-on experience with AWS cloud services, such as S3, Lambda, for managing ML workflows, understanding of software development principles, including design patterns, testing, and deployment, Experience with DevOps practices such as CI/CD, experience with containerization using Docker and Kubernetes, understanding of application implementation requirements, including risk, privacy, and compliance, Excellent communication skills with the ability to work effectively with cross-functional teams

Nice to Have

Past experience in data and AI/ML space, Graduate in science, mathematics, statistics or engineering

What You'll Do.

Develop and Optimize Machine Learning Models

Ensure Scalable Model Deployment

Collaborate with Cross-functional Teams

Streamline Pipeline Releases

Maintain and Monitor Model Performance

Document and Share Knowledge

Maintain and Monitor production applications

Enhance Operational Efficiency

Emerging Technology research and application

How You'll Work.

Team & Collaboration

collaborate with cross-functional teams; collaborate closely with team members under Agile Squad including product owners, Data Scientists, Designers, Quality Engineers and other ML Engineers; work closely with data scientists, product managers and software engineers; share knowledges with teams

Communication Scope

Excellent communication skills; Verbal and written communication skills

Full Job Description

**_Job Description_** **What is the opportunity?** The Senior AI Engineer will work on the development and deployment of cutting-edge machine learning models, drive innovation, and collaborate with cross-functional teams to drive business growth and improvement. The candidate will have a strong background in machine learning models and algorithms, software development and leadership, with a proven track record of delivering high-quality solutions that meet business needs. The person will collaborate closely with team members under Agile Squad including product owners, Data Scientists, Designers, Quality Engineers and other ML Engineers. **What will you do?** * **Develop and Optimize Machine Learning Models:** refine predictive models tailored for Caribbean use cases such as document automation, customer segmentation or risk assessment. * **Ensure Scalable Model Deployment:** implement robust ML pipelines that enable the seamless deployment of models into production while ensuring scalability, reliability, and minimal downtime. * **Collaborate with Cross-functional Teams:** work closely with data scientists, product managers and software engineers to integrate AI models into existing Caribbean workflows and applications. * **Streamline Pipeline Releases:** build automated CI/CD pipelines for ML model lifecycle management, ensuring efficient testing, versioning, and deployment of new features or updates. * **Maintain and Monitor Model Performance:** continuously evaluate deployed models’ performance, accuracy, and fairness. Implement monitoring systems to detect and mitigate model drift or biases. * **Document and Share Knowledge** : maintain comprehensive documentation of models, pipelines, and processes. * **Maintain and Monitor production applications:** participate in SRE setup to support end-to-end application in production. Ready to provide after hour support on need basis * **Enhance Operational Efficiency** : keep software engineering practice in mind, build p

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