Job Summary
Job Description
What is the opportunity?
Are you a talented, creative, and results-driven professional who thrives on delivering high-performing applications. Come join us!
Global Functions Technology (GFT) is part of RBC’s Technology and Operations division. GFT’s impact is far-reaching as we collaborate with partners from across the company to deliver innovative and transformative IT solutions. Our clients represent Risk, Finance, HR, CAO, Audit, Legal, Compliance, Financial Crime, Capital Markets, Personal and Commercial Banking and Wealth Management. We also lead the development of digital tools and platforms to enhance collaboration.
Senior Machine Learning Engineer is responsible for developing application for large-scale data processing and analysis. You will work with all stakeholders to design best in class technology solutions. We value positive attitude, willingness to learn, open communication, teamwork, and commitment to clean, secure and well-tested code.
As a Machine Learning Engineer, you will be a part of the EDA team, developing applications for large-scale data processing and analysis performing data modeling and building the data infrastructure that powers effective decision-making. You will be working in a cross functional team that supports various businesses and you will have an opportunity to work with different kinds of datasets. You will collaborate with other developers and business partners to deliver medium – high complexity initiatives aligned with EDA and GFT strategic objectives.
What will you do?
- Productionize, optimize ML based or any other advanced analytics models and algorithms tailored to address precise business challenges.
- A/B testing with renewed change management, and iteratively improve model accuracy and overall solution efficiency.
- E2E technical competency including conducting data analysis, data preprocessing, and feature engineering to prepare datasets for model training.
- Work alongside data scientists, quantitative analysts, software engineers, data engineers, and domain experts to collect requirements and establish project goals.
- Document machine learning processes, methodologies, and results to facilitate knowledge sharing and collaboration.
What do you need to succeed?
Must Have
- Have a minimum of 5 years of experience in software development, with a strong focus on Python programming.
- Experience in working with cross-functional teams to deliver results
- Possess professional working experience with LLMs, RAG, transformers, TensorFlow, PyTorch, BERT and cross encoding models
- Having demonstrated a solid foundation in data structures, algorithms, and software engineering principles, with a track record of developing high-quality, maintainable code.
- Should be familiar with recent LLMs and development frameworks, i.e. OpenAI, Llama, Mistral, LangChain etc.
- Proven Machine Learning industry experience, preferably at scale.
- Prior experience with transfer learning and model modifications.
- Excellent problem-solving skills, while exhibiting high enthusiasm to tackle complex challenges in AI/ML development and deployment.
- Are enthusiastic about working in a fast-paced, innovative environment, contributing to a team that aims to make a significant impact in the banking and finance technology space
- Database and programming languages experience and data manipulation and integration skills using (one or more) SQL, NoSQL Databases, or similar tools is required
- Possess good understanding on leveraging Azure's AI and machine learning services to deploy, monitor, and maintain ML models, ensuring high availability and performance.
Nice to Have
- Knowledge of machine learning and data science concepts and tools.
- Knowledge of any other programming languages such as Javascript or Java
- Understanding and passion for machine learning/AI
- Experience working with at least one of Snowflake, PostgreSQL, and/or other DBMS platforms
What’s in it for you?
We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.
- 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
- 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.
#LI-Hybrid
#LI-Post
#LI-PK
Job Skills
Big Data Management, Data Modeling, Data Science, Decision Making, Deep Learning, Logical Data Modeling, Machine Learning, Machine Learning Algorithms, Machine Learning Techniques, Predictive Analytics, Programming Languages, Regression Models, Relationship Building, Statistical AnalysisAdditional 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
Inclusion and Equal Opportunity Employment
At RBC, we embrace diversity and inclusion for innovation and growth. We are committed to building inclusive teams and an equitable workplace for our employees to bring their true selves to work. We are taking actions to tackle issues of inequity and systemic bias to support our diverse talent, clients and communities.
We also strive to provide an accessible candidate experience for our prospective employees with different abilities. Please let us know if you need any accommodations during the recruitment process.
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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.
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