Senior AI Engineer

RBC•Toronto, ON

9d•Onsite

About The Position

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.

Requirements

Strong programming skills in languages such as Python, java, or C++.
Experience with cloud platforms (AWS, GCP, and Azure) and MLOps tools.
Core Machine Learning and AI Skills with 2 + years of hands-on experience in model development and optimization, with knowledge of advance ML techniques.
Hands-on experience with frameworks like Hugging Face Transformers, LangChain, or OpenAI APIs
Natural Language Processing (NLP): strong understand of NLP tasks such as entity recognition, summarization, text classification. Skills in evaluating LLM performance using metrics
Data Pipeline and Workflow: proficiency in creating, maintaining, and troubleshooting DAGs for scheduling and orchestrating ML workflows. Experience in integrating Airflow with cloud data storage and ETL pipelines.
Past experience in data and AI/ML space would be preferred
Experience with data pipelines using tools like Apache Spark or Pandas for handling structured and unstructured data.
Cloud and Infrastructure: 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.
Strong 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.
Strong 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 Haves

Adaptability, Critical thinking and growing mindset
Management and collaboration skills, Verbal and written communication skills
Team contributor and care about team members
Graduate in science, mathematics, statistics or engineering

Responsibilities

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 products that can be maintain with least incidents, maintain metrics and monitoring to meet Service and Operational Level Agreements.
Emerging Technology: stay up-to-date with the latest advancements in machine learning and related emerging technologies, share knowledges with teams and apply the knowledge to improve existing systems and develop new ones.

Benefits

A comprehensive Total Rewards Program including bonuses and flexible benefits
competitive compensation
commissions
stock where applicable
Leaders who support your development through coaching and managing opportunities
Ability to make a difference and lasting impact
Work in a dynamic, collaborative, progressive and high-performing team
A world-class training program in financial services
Flexible work/life balance options
Opportunities to do challenging work
Opportunities to take on progressively greater accountabilities
Opportunities to building close relationships with clients
Access to a variety of job opportunities across business and geographies