{bc}
indeed

Senior AI Engineer

RBC
Toronto, CAN
Full Time
Senior
1 weeks ago
PythonJavaC++AWSGCPAzure
Free

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Opportunity Overview

  • The Senior AI Engineer will develop and deploy cutting edge machine learning models, drive innovation, and collaborate with cross functional teams.
  • The candidate will have a strong background in ML models, software development, and leadership, with a proven track record of delivering high quality solutions.

What will you do?

  • Develop and optimize machine learning models tailored for Caribbean use cases such as document automation, customer segmentation or risk assessment.
  • Implement robust ML pipelines for seamless deployment into production ensuring scalability, reliability, and minimal downtime.
  • Collaborate with data scientists, product managers and software engineers to integrate AI models into existing Caribbean workflows.
  • Build automated CI/CD pipelines for ML model lifecycle management, ensuring efficient testing, versioning, and deployment.
  • Continuously evaluate deployed models’ performance, accuracy, and fairness; implement monitoring to detect and mitigate drift or biases.
  • Maintain comprehensive documentation of models, pipelines, and processes.
  • Participate in SRE setup to support end to end application in production; provide after hours support as needed.
  • Build products maintainable with least incidents; maintain metrics and monitoring to meet Service and Operational Level Agreements.
  • Stay up to date with latest advancements in machine learning and share knowledge with teams.

Must Have

  • Strong programming skills in Python, Java, or C++.
  • Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools.
  • 2+ years hands on experience in model development and optimization with knowledge of advanced ML techniques.
  • Hands on experience with Hugging Face Transformers, LangChain, or OpenAI APIs.
  • Strong understanding 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 (e.g., Airflow).
  • Experience with data pipelines using Apache Spark or Pandas.
  • Experience with AWS SageMaker and AWS cloud services (S3, Lambda).
  • Strong understanding of software development principles, DevOps practices (CI/CD), Docker, and Kubernetes.
  • Strong understanding of application implementation requirements including risk, privacy, and compliance.
  • Excellent communication skills and ability to work effectively with cross functional teams.

Nice to Have

  • Adaptability, critical thinking and growing mindset.
  • Management and collaboration skills, verbal and written communication skills.
  • Team contributor and care about team members.
  • Graduate degree in science, mathematics, statistics or engineering.

What’s in it for you?

  • Comprehensive Total Rewards Program including bonuses, flexible benefits, competitive compensation, commissions, and 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.
  • World class training program in financial services.
  • Flexible work/life balance options.
  • Opportunities to do challenging work and take on progressively greater accountabilities.
  • Access to a variety of job opportunities across business and geographies.

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