Senior AI Engineer
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Key skills for this role
About the Role
RBC is seeking a Senior AI Engineer to develop and deploy cutting-edge machine learning models for Caribbean use cases. You will build ML pipelines, collaborate with cross-functional teams, and ensure scalable model deployment.
Key Skills for This Role
Responsibilities
- Develop and optimize machine learning models for Caribbean use cases such as document automation, customer segmentation or risk assessment
- Implement robust ML pipelines for seamless deployment of models into production ensuring scalability and reliability
- Collaborate with data scientists, product managers and software engineers to integrate AI models into existing workflows
- Build automated CI/CD pipelines for ML model lifecycle management
- Continuously evaluate deployed models’ performance, accuracy, and fairness; implement monitoring for model drift
- Maintain comprehensive documentation of models, pipelines, and processes
- Participate in SRE setup to support end to end application in production; provide after hour support as needed
- Build products that can be maintained with least incidents; maintain metrics and monitoring to meet SLAs
- Stay up to date with latest advancements in machine learning and share knowledge with teams
Requirements
- Strong programming skills in Python, Java, or C++
- Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools
- 2+ years of hands on experience in model development and optimization, with knowledge of advanced ML techniques
- Hands on experience with frameworks like 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 integrating Airflow with cloud data storage and ETL pipelines
- Experience with data pipelines using tools like Apache Spark or Pandas
- Hands on experience with 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
Full Job Posting
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.
- 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 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.
What do you need to succeed?
- 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.
- Adaptability, Critical thinking and growing mindset (nice to have).
What’s in it for you?
- A comprehensive Total Rewards Program including bonuses and 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.
- 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.
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