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Insurance Learning Development Jobs in Toronto, ON

Tobermory

Machine Learning Engineer

Richmond Hill, ON · On-site

CA$76K - CA$138K/yr

Health coverage, dental care, vision coverage, life insurance, disability protection, RRSP matching ... Review developments in audio machine learning, signal processing and deep learning. * Apply ...

New

BGBx

Art Supervisor

Toronto, ON · On-site

CA$100K - CA$116K/yr

Our benefits package typically includes health care insurance, retirement plans, generous paid time off and holidays, wellness benefits, life insurance, learning and development opportunities, and ...

HollisWealth

Damage Insurance Agent

Toronto, ON · Hybrid

CA$52K/yr

As a learning organization, iA invests in the continuous development of its agents by promoting learning, knowledge sharing, and adaptation to the evolving insurance industry. Don't have your AMF ...

BMO Capital Markets

Development Manager

Toronto, ON · On-site

CA$85K - CA$185K/yr

Learning Agility. * Building and managing relationships. * Technical writing / documentation ... BMO also offers health insurance, tuition reimbursement, accident and life insurance, and ...

BMO Capital Markets

Development Manager

Toronto, ON · On-site

CA$85K - CA$185K/yr

Learning Agility. * Building and managing relationships. * Technical writing / documentation ... BMO also offers health insurance, tuition reimbursement, accident and life insurance, and ...

BGBx

Senior Project Manager

Brampton, ON · On-site

Our benefits package typically includes health care insurance, retirement plans, generous paid time off and holidays, wellness benefits, life insurance, learning and development opportunities, and ...

BGBx

Senior Project Manager

Hamilton, ON · On-site

Our benefits package typically includes health care insurance, retirement plans, generous paid time off and holidays, wellness benefits, life insurance, learning and development opportunities, and ...

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All JobsInsurance Learning Development JobsInsurance Learning Development Jobs in Toronto, ON

Insurance Learning Development information

What is Insurance Learning Development?

Insurance Learning Development refers to the processes and strategies used to train, educate, and develop skills for employees within the insurance industry. This includes creating training programs, managing e-learning platforms, and ensuring staff stay current with regulations and industry best practices. Professionals in this field work closely with subject matter experts to design courses on topics like underwriting, claims management, compliance, and customer service. The goal is to enhance employee performance, maintain compliance, and improve overall organizational effectiveness.

What are the key skills and qualifications needed to thrive in Insurance Learning Development?

To excel in Insurance Learning Development, you need a solid understanding of insurance products, adult learning principles, and instructional design, typically backed by a degree in education, business, or a related field. Familiarity with learning management systems (LMS), e-learning authoring tools, and certifications such as CPLP or L&D-focused credentials are commonly required. Excellent communication, creativity, and the ability to adapt training methods to diverse audiences will help you stand out. These skills ensure effective training delivery that enhances employee performance and supports organizational compliance and growth.

What are the main challenges faced by professionals in Insurance Learning Development, and how can they be addressed?

Professionals in Insurance Learning Development often face the challenge of keeping training materials current with evolving regulations and complex insurance products. Additionally, engaging a diverse workforce with varying levels of experience requires innovative instructional strategies and adaptive delivery methods. Building strong collaboration with subject matter experts and regularly seeking feedback from learners can help ensure training programs are both accurate and effective. Staying updated with industry trends and leveraging technology for e-learning also supports continuous improvement in this role.

What is the difference between Insurance Learning Development vs Insurance Training Coordinator?

AspectInsurance Learning DevelopmentInsurance Training Coordinator
CertificationsTypically requires industry certifications and instructional design credentialsMay require basic insurance or training certifications
Work EnvironmentDesigns and develops training programs, often in corporate or educational settingsCoordinates and delivers training sessions, often within insurance companies or agencies
Employer & Industry UsageUsed by insurance companies, corporate training firms, and educational institutionsCommonly employed by insurance firms, brokerages, and training providers

Insurance Learning Development focuses on creating and implementing comprehensive training programs, often involving instructional design and curriculum development. In contrast, an Insurance Training Coordinator primarily manages the delivery and coordination of training sessions. Both roles support employee education but differ in scope and responsibilities.

What job categories do people searching Insurance Learning Development jobs in Toronto, ON look for?

The top searched job categories for Insurance Learning Development jobs in Toronto, ON are:

Insurance Learning Development jobs near you
Infographic showing various Insurance Learning Development job openings in Toronto, ON as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Machine Learning Engineer

Richmond Hill, ON • On-site

Tobermory
See more jobs at Tobermoryexternal

CA$76K - CA$138K/yr

Other

Medical, Dental, Vision, Life, PTO

Posted 3 days ago

New

Job description

Machine Learning Engineer, NVH develops advanced machine learning systems that help Tesla improve product diagnostics and quality across its vehicles and technologies. Based in Richmond Hill, this role combines artificial intelligence, audio processing and engineering to create tools that support manufacturing and customer satisfaction.

The role is about building diagnostic models, managing those data pipelines and getting machine learning solutions out of the lab and into real production environments. You will work across teams in manufacturing, quality and vehicle engineering and the work feeds straight into how Tesla spots product issues and tackles them at scale.

Tesla gives you the chance to engage with tough technology that really affects its products and customers world wide. Check the job details below to get more context.

Company Name : Tesla
Location : Richmond Hill, Ontario, Canada
Salary : $76,000 – $138,000/annually
Job Type : Full time
Start date : As soon as possible
Benefits : Health coverage, dental care, vision coverage, life insurance, disability protection, RRSP matching contributions, employee stock purchase plan, employee assistance resources, parental support programs, paid sick leave, vacation time, paid holidays, Tesla family benefits, product savings, wellness discounts and additional employee rewards.

Job Description
  • Machine Learning Engineer, NVH is a machine learning and software engineering role within Tesla’s Noise, Vibration and Harshness team.
  • This is a full time position based in Richmond Hill, Ontario.
  • The role focuses on developing diagnostic systems for Tesla vehicles and products.
  • The position combines machine learning, audio processing and production deployment work.
  • The work environment is research driven, technology focused and team oriented.
  • Employees receive competitive compensation, stock awards, benefits and access to innovative engineering projects.
Responsibilities
  • Design, develop and deploy machine learning models and audio algorithms for NVH diagnostics.
  • Build and maintain machine learning pipelines from data collection through production deployment.
  • Work with manufacturing, quality audit and vehicle engineering teams to integrate diagnostic systems.
  • Improve model performance through testing, experimentation and iterative development.
  • Develop tools and frameworks for collecting data, labelling and model monitoring.
  • Work to develop coding standards, testing practices, documentation and reproducibility.
  • Review developments in audio machine learning, signal processing and deep learning.
  • Apply relevant research advancements to Tesla’s diagnostic challenges.
Requirements
  • A degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science or a related field is required, or equivalent work background.
  • Strong knowledge of Python and C++ is required.
  • Solid background in software engineering practices including version control, testing and code review is required.
  • Strong knowledge of machine learning fundamentals including neural networks, optimization methods, regularization and model evaluation is required.
  • Work background with neural network architectures for audio applications including CNNs, RNNs and Transformers is required.
  • Strong knowledge of event detection and of classification models.
  • Skilled in PyTorch or another major deep learning tool such as TensorFlow.
  • Can work with machine learning systems from development through deployment in production environments.
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