Sobre esta vaga de Staff ML Engineer na RBC
Job Description
What is the opportunity?
This is an opportunity to work at RBC Wealth Management Technology Data team with a group of technology professionals dedicated to delivering transformative ML solutions to Wealth business and clients. We are all in with Agile development, DevOps, Open Source, Software as a Service (SaaS) and modern tools and processes.
We are looking for an experienced and visionary Staff Data Engineer to spearhead advanced ML initiatives, lead end-to-end project delivery, manage and mentor a high-performing ML engineering team, and drive technical innovation across the Wealth Management data domain.
The ideal candidate will have:
End-to-End Production Software Development Expertise: A proven track record of designing, building, and deploying scalable production applications and APIs from conception through maintenance, with deep understanding of software architecture, performance optimization, and operational excellence
Data Product Development & Deployment Mastery: Demonstrated experience leading the full lifecycle of data-driven products—from ideation and development to deployment and optimization—with ability to translate business requirements into scalable data product solutions that drive measurable value
Advanced Machine Learning Integration Capabilities: Deep expertise in integrating Machine Learning models and GenAI solutions with WM data and business systems, with proven success in deploying ML-powered features to production environments
Strong Background in Technical Leadership: Experience managing and mentoring technical teams, providing technical direction, and fostering high-performing cultures of innovation and continuous improvement
Deep Understanding of Modern Data and Cloud Ecosystems: Proficiency in modern data stacks, cloud computing platforms (AWS/Azure), containerization, microservices architecture, and the ability to architect scalable solutions that meet enterprise requirements
Ability to Shape Strategy and Drive Innovation: Proven capability to define technical roadmaps, establish best practices, and lead cross-functional initiatives that align technical solutions with organizational business objectives and drive competitive advantage
You will play a pivotal role in building and scaling our ML capabilities while partnering with IT and business stakeholders to assess, research, and resolve critical business challenges through technology solutions.
What will you do?
Team Leadership & Mentorship
Manage and lead a team of ML engineers and data engineers, providing technical guidance, mentorship, and career development
Foster a high-performing culture of innovation, collaboration, and continuous learning
Conduct performance evaluations and provide constructive feedback to team members
Hire and build diverse, talented teams aligned with organizational goals
Technical Strategy & Direction
Own end-to-end ML project delivery, from conception through production deployment and optimization
Define and communicate technical roadmap and architecture for ML initiatives aligned with business objectives
Provide technical direction and set standards for ML development practices, code quality, and MLOps
Make critical technical decisions that balance innovation, scalability, and risk management
Partner with architects, product managers, and business leaders to evaluate use cases and align ML initiatives with company goals
Production-Level Software Development
Design, build, and deploy scalable, production-grade applications and APIs that integrate WM data with advanced capabilities
Establish best practices for code quality, testing, validation, monitoring, and continuous improvement
Oversee end-to-end software pipelines ensuring seamless integration with applications and data platforms
Collaborate with software engineers to ensure robust, maintainable, and well-documented code
Data Product Development and Deployment
Lead the development and deployment of data-driven products that deliver measurable business value to Wealth business and clients
Build comprehensive data pipelines and architectures that enable scalable product features
Establish monitoring and metrics systems to measure product performance against Service and Operational Level Agreements (SLAs)
Drive continuous optimization of data products based on performance metrics and user feedback
Cross-Functional Collaboration
Act as primary technical liaison with multiple RBC teams, stakeholders, executives, and third-party vendors
Collaborate with Agile teams, product owners, software engineers, and business stakeholders
Communicate complex ML concepts to non-technical audiences and translate business needs into technical solutions
Drive organizational alignment on ML priorities and technical capabilities
Continuous Learning & Innovation
Stay at the forefront of emerging ML technologies, cloud advancements, and industry best practices
Share knowledge with teams and drive adoption of new techniques to improve existing systems
Contribute to thought leadership within RBC and the broader ML community
What do you need to succeed?
Must Have
6+ years of experience building scalable production APIs/microservices (Python preferred), with 2+ years in leadership or mentorship
Expert-level proficiency in cloud platforms: AWS and/or Azure, with OpenShift containerization experience
Strong expertise in GenAI and Machine Learning service integrations.
Proficiency in data engineering: data cataloging, schema management, data quality, data lineage, data governance, ELT/ETL pipelines, and data streaming.
Excellent business communication skills—able to explain complex technical concepts to non-technical stakeholders and vice versa.
Experience collaborating with architects to brainstorm and design solutions that meet business requirements.
Production-Level Software Development Experience: Proven track record of shipping and maintaining high-volume production applications.
API-First Mindset: Strong emphasis on designing and developing robust, scalable APIs and data pipelines.
Business Acumen & Cross-Functional Leadership: Ability to understand design requirements and lead technical initiatives across multiple teams, aligning business goals with technical solutions.
Learning Agility: Staying current with emerging data engineering technologies, especially in GenAI and ML.
Nice to Have
Understanding of IT Standards, Methodologies, CMM & audit requirements
Financial institution and Wealth Management domain knowledge
Advanced ML techniques (NLP, deep learning, reinforcement learning)
Knowledge of modern data platforms and architectures (data lakes, data warehouses, streaming platforms)
Experience with Agile and Scrum methodologies
What’s in it for you?
A comprehensive Total Rewards Program including bonuses, flexible benefits, and competitive compensation
Leaders who support your development and growth through coaching and strategic opportunities
The ability to make a significant, lasting impact on RBC’s ML strategy and technical capabilities
Work in a dynamic, collaborative, progressive, and high-performing team
A world-class training program in financial services
Opportunities to lead challenging, high-visibility projects
Opportunities to take on progressively greater responsibilities and strategic influence
Access to a variety of career advancement opportunities across RBC’s business units and geographies
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Job Skills
Big Data Management, Data Mining, Data Science, Deep Learning, Machine Learning (ML), Predictive Analytics, Programming LanguagesAdditional Job Details
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Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above
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