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Machine Learning Software Engineer information
See Alberta salary details
$82K - $97.5K
9% of jobs
$113K is the 25th percentile. Wages below this are outliers.
$97.5K - $113K
16% of jobs
$113K - $128.5K
13% of jobs
The median wage is $140.9K / yr.
$128.5K - $144K
16% of jobs
$144K - $159.5K
5% of jobs
$159.5K - $175K
13% of jobs
$180.6K is the 75th percentile. Wages above this are outliers.
$175K - $190.5K
11% of jobs
$190.5K - $206K
13% of jobs
$206K - $221.5K
1% of jobs
$221.5K - $237K
0% of jobs
$237K - $252.5K
4% of jobs
$82K
$154.6K
$252.5K
How much do machine learning software engineer jobs pay per year?
What does a Machine Learning Software Engineer do?
A Machine Learning Software Engineer designs, develops, and deploys machine learning models within software applications. They work on data preprocessing, model training, optimization, and integration into production systems. Their role requires expertise in programming (Python, Java, or C++), machine learning frameworks (TensorFlow, PyTorch, or Scikit-learn), and cloud platforms. They collaborate with data scientists and software engineers to build scalable ML solutions.
What are the key skills and qualifications needed to thrive in the Machine Learning Software Engineer position, and why are they important?
To thrive as a Machine Learning Software Engineer, you need a solid understanding of programming (especially Python), algorithms, data structures, and mathematics, ideally backed by a degree in computer science, engineering, or a related field. Experience with frameworks such as TensorFlow or PyTorch, familiarity with cloud platforms (AWS, Azure, or GCP), and relevant certifications in data science or machine learning are highly valuable. Strong problem-solving skills, effective communication, and the ability to work collaboratively with cross-functional teams set outstanding candidates apart. These competencies are crucial for building deployable, scalable, and maintainable machine learning solutions that address real business challenges.
What are the day-to-day responsibilities of a Machine Learning Software Engineer?
As a Machine Learning Software Engineer, your daily tasks typically include developing and optimizing machine learning models, collaborating with data scientists and product teams to define requirements, and integrating models into production systems. You’ll work extensively with large datasets to preprocess, analyze, and validate data, as well as monitor model performance and iterate on solutions when needed. It's common to participate in code reviews, contribute to architectural decisions, and maintain documentation for reproducibility and knowledge sharing. This role offers a dynamic and intellectually stimulating environment, making it ideal for those who enjoy solving complex technical problems and working at the intersection of engineering and data science.
Job description
Job Description
At RBC Borealis, you'll be joining a team of leading researchers and software engineering specializing in machine learning. You will have access to rich and massive datasets, and to computational resources to support novel product development touching machine learning areas such as generative AI, natural language processing, and time series analysis.
We're looking for an enthusiastic Machine Learning Researcher who's excited by the opportunity of being at the forefront of applying machine learning technology to challenging problems. As a Machine Learning Researcher, you're looking to channel your love of playing with real-world data into industry-disrupting solutions. We're a lab that supports research on a wide variety of theoretical and applied machine learning projects. Working in our lab will grant you unique access to massive structured and unstructured datasets with the tools and resources necessary to build game-changing statistical models.
Being part of our team means you'll also have the opportunity to publish original research in peer-reviewed academic journals and participate in conferences around the world, such as NeurIPS, ICLR, ICML, CVPR and more.
Your responsibilities include:
Developing novel AI solutions that facilitate impactful products;
Conducting original, publishable research by advancing the state-of-the-art in machine learning techniques;
Working with the development team to transfer research work into production;
Interpreting larger organizational needs and designing algorithmic solutions that can drive the next generation of banking experiences;
Identifying relevant new AI technologies as they become available, and disseminating them into the bank's technology capabilities.
You're our ideal candidate if you have:
A passion for solving open problems using data and algorithms;
A PhD in a sub-area of AI or demonstrated research track record by means of publications and/or sophisticated AI product experience;
Ability to formulate and drive a research project independently without close supervision;
Proficiency in Python and Deep Learning packages such as Tensorflow or PyTorch.
What's in it for you?
Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;
A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable;
Leaders who support your development through coaching and managing opportunities;
Ability to make a difference and lasting impact from a local-to-global scale.
About RBC Borealis
RBC Borealis, an RBC Institute for Research, is a curiosity-driven research centre dedicated to achieving state-of-the-art in machine learning. Established in 2016, and with labs in Toronto, Montreal, Waterloo, and Vancouver, we support academic collaborations and partner with world-class research centres in artificial intelligence. With a focus on ethical AI that will help communities thrive, our machine learning scientists perform fundamental and applied research in areas such as reinforcement learning, natural language processing, deep learning, and unsupervised learning to solve ground-breaking problems in diverse fields.
Inclusion and Equal Opportunity Employment
RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.
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Job Skills
Analytical Thinking, Decision Making, Detail-Oriented, Long Term Planning, Machine Learning (ML), Product Development Design, Programming Languages, Quantitative Research, Research and Development Operations, Research DocumentsAdditional Job Details
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Our Employment Opportunities
At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.
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RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.
Employment Type: FULL_TIMEAbout Royal Bank of Canada
Sourced by ZipRecruiter
Industry
Banking and credit intermediation
Company size
10,000+ Employees
Headquarters location
Toronto, Ontario, CA