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Deep Learning Developer Jobs in Ontario (NOW HIRING)

What You'll Need to Succeed To be considered, you'll need strong hands-on experience as a Machine Learning Engineer with deep exposure to time series forecasting and applied ML in production settings.

Research Engineer

Toronto, ON · On-site +1

CA$122K - CA$215K/yr

You will work closely with our team of world-renowned scientists and engineers specializing in deep learning, computer vision, and self-driving technologies to develop cutting-edge solutions that ...

D. in Computer Science, Engineering, Mathematics, or a related quantitative field. * 5+ years of applied deep learning experience with end-to-end ownership of complex modelling initiatives. * Strong ...

Faculte de genie / Faculty of Engineering Academic Unit: Ecole de conception et d'innovation ... Deep understanding of Big Data Analytics tools especially Hadoop and Spark. Hands-on knowledge of ...

You will work closely with our team of world-renowned scientists and engineers specializing in deep learning, computer vision, and self-driving technologies to develop cutting-edge solutions that ...

Data Engineer and Generative AI/ML Specialist Skill Cluster/Practice: Data Engineering / Emerging ... Apply and productionize Machine Learning and Deep Learning models, including building ...

Data Engineer and Generative AI/ML Specialist Skill Cluster/Practice: Data Engineering / Emerging ... Apply and productionize Machine Learning and Deep Learning models, including building ...

AI Engineer, AidenSales RBC Capital Markets is seeking an AI Engineer with deep expertise in Generative AI, neural networks, and transfer learning to support Sales teams with cutting-edge AI-powered ...

AI Engineer, AidenSales RBC Capital Markets is seeking an AI Engineer with deep expertise in Generative AI, neural networks, and transfer learning to support Sales teams with cutting-edge AI-powered ...

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Deep Learning Developer information

What are the key skills and qualifications needed to thrive as a Deep Learning Developer, and why are they important?

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What are Deep Learning Developers?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

Which 3 jobs will survive AI?

Deep Learning Developers are likely to continue to be in demand as AI advances because they design and improve AI models, requiring specialized skills in programming, mathematics, and data analysis. Other resilient roles include AI ethicists, who address ethical considerations, and AI system trainers, who curate and annotate data to improve AI performance. These jobs involve complex problem-solving and human oversight that are less easily automated.

What is the difference between Deep Learning Developer vs Machine Learning Engineer?

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What are some common challenges Deep Learning Developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.
What cities in Ontario are hiring for Deep Learning Developer jobs? Cities in Ontario with the most Deep Learning Developer job openings:
Infographic showing various Deep Learning Developer job openings in Ontario as of June 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 88% Full Time, 3% Part Time, 3% Temporary, and 4% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution.
Senior Data Scientist

Full-time

Posted 18 hours ago


Job description

Job Description

WHAT IS THE OPPORTUNITY?

RBC Technology Infrastructure seeks a full stack Data Scientist (DS) to explore and operationalize big data sources to reduce outage and down time for RBC services that leads to improve user experience and save costs. Seeking a DS with experience in applied research and problem solving to join our team. The successful candidate will have experience with developing and deploying production grade AI/ML solutions, have broad expertise in statistics, analytics, ML and strong programming skill.

WHAT WILL YOU DO?

  • Lead full life-cycle Data Science solutions from beginning to model deployment and monitoring and partner with the engineering team to ensure best practices for ML model deployment.
  • Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.
  • Experience in (Python, Apache Spark, PySpark, R, Scala, SQL, NoSQL, etc.) to obtain, integrate, manipulate, and analyze data from multiple sources.
  • Expertise in statistical data analysis (e.g. univariate/bivariate analysis) and data quality assessment.
  • Build Machine Learning, Deep Learning and statistical models to solve specific business problems.
  • Developing predictive data models, anomaly detection model, quantitative analyses and visualization of targeted big data sources.
  • Leading data exploration and analytic projects and providing on-going coaching of big data topics (visualization, data mining, analytic techniques).
  • Exploring and implementing semantic data capabilities through NLP, text mining and machine learning techniques.
  • Overseeing the acquisitions and ingestions of data from structured and unstructured sources, while ensuring quality and comprehensiveness of data.
  • Utilizing APIs to collect data from various products into the Data Warehouse Database.

WHAT DO YOU NEED TO SUCCEED?

Must have:

  • 5+ years of industry experience required working on real-world problems. University, Master or Ph.D. degree in an analytical field of study(e.g. Computer Science, Engineering, Mathematics, Statistics, or related quantitative field).
  • Experienced with AI/ML infrastructure and model deployment for Gen AI applications in production environments and supporting enterprise-scale use cases
  • Strong foundation in ML and AI basics, knowledge of Inferencing, fine-tuning, model architectures, Embeddings. Hands-on experience implementing solutions using modern ML and Deep Learning frameworks, such as PyTorch, TensorFlow, Scikit-Learn, or Hugging Face Transformers
  • Hands-on experience designing graph data models and working with graph databases (Neo4j, Amazon Neptune, TigerGraph) and/or knowledge graph frameworks (RDF/OWL, property graphs, SPARKQL)
  • Familiar with software engineering industry best practices, including coding standards, testing methods, code reviews, and version control
  • Experience working with technical and non-technical project stakeholders to scope, formulate, deploy, and maintain data science systems.
  • Self-driven problem solver, able to adapt and thrive in a dynamic, ambiguous, and customer-faced environment.
  • Familiarity with GIT (GitHub)
  • Strong communication, collaboration, and problem-solving skills.
  • Ability to prioritize work and manage multiple work streams concurrently.
  • In-depth knowledge in machine learning and deep learning algorithms.
  • Excellent working with structured and non-structured data. Excellent knowledge in Python, PySpark, SQL.
  • Experience with cloud-based data platforms such as Azure or AWS. Experience with data visualization tools such as Tableau, Looker, and Power BI.

Nice-to-have:

  • Experience architecting large scale ML systems.
  • Experience working knowledge of Reinforcement learning (DynaQ/Q+, SARSA, TD, Monte Carlo).
  • Experience with GenAI LLM models.
  • Experience with MLOps workflow.
  • Knowledge in AIOps domain.
  • Knowledge of IT Operation Monitoring Tools (Dynatrace, Moog, GEM, Pager Duty, etc )

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-Post

#TechPJ

Job Skills

Actuarial Modeling, Big Data Management, Commercial Acumen, Data Mining, Data Science, Decision Making, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language)

Additional Job Details

Address:

RBC CENTRE, 155 WELLINGTON ST W:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-04-01

Application Deadline:

2026-06-30

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

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_TIME