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Aws Machine Learning Jobs in British Columbia (NOW HIRING)

Machine Learning Engineer

Vancouver, BC · On-site

$128 - $192/hr

About the Role As a Machine Learning Engineer on the AI Platform Context and Retrievals team, you ... AWS, GCP, etc.) Other Qualifications * 3+ years of professional experience in building information ...

Senior Machine Learning Engineer

Burnaby, BC · On-site

CA$168K - CA$210K/yr

As a Senior Machine Learning Engineer in Remitly's Core AI/ML team, you'll work at the heart of our ... Experience working with major cloud platforms (AWS, GCP, or Azure). * Experience with one or more ...

Extensive experience with at least one major cloud platform, AWS preferred * Strong proficiency in ... Machine Learning engineering practices. You will act as a technical partner and lead by example ...

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Aws Machine Learning information

See British Columbia salary details

$24K

$127.8K

$211K

How much do aws machine learning jobs pay per year?

As of Aug 24, 2026, the average yearly pay for aws machine learning in British Columbia is $127,790.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,500.00 and $162,000.00 per year, depending on experience, location, and employer.

What is an AWS Machine Learning?

An AWS Machine Learning job involves designing, building, and deploying machine learning models using Amazon Web Services (AWS) cloud infrastructure. Professionals in this role work with services like Amazon SageMaker, AWS Lambda, and AWS Glue to develop AI-driven applications. They optimize models for scalability, integrate them into cloud-based systems, and ensure efficient data processing. Strong knowledge of machine learning algorithms, AWS architecture, and MLOps best practices is essential for success in this role.

What does an AWS Machine Learning do?

In an AWS Machine Learning position, you'll typically design, develop, and deploy machine learning models using AWS services like SageMaker, Glue, and Lambda. Daily tasks often include data preprocessing, building and training models, and optimizing performance for production environments. You'll collaborate closely with data engineers, software developers, and business analysts to translate business needs into technical solutions. The role may also involve monitoring deployed models, managing cloud resources, and staying updated on new AWS features to ensure efficient and scalable machine learning workflows.

What are the key skills and qualifications needed for an AWS Machine Learning?

To thrive as an AWS Machine Learning professional, you need a strong understanding of machine learning principles, proficiency in programming languages like Python, and experience with AWS cloud services such as SageMaker. AWS Certified Machine Learning certification and familiarity with data pipelines, EC2, and Lambda are commonly required. Strong problem-solving, communication, and teamwork skills help you translate business requirements into technical solutions and collaborate effectively with diverse stakeholders. These skills are essential to efficiently deploy and manage scalable machine learning models that deliver business value in cloud-based environments.

Does AWS use machine learning?

AWS offers a wide range of machine learning services and tools, such as Amazon SageMaker, which enable developers and data scientists to build, train, and deploy machine learning models. As a cloud provider, AWS integrates machine learning into its infrastructure to support various applications, making it a key platform for machine learning professionals. Knowledge of AWS services and machine learning concepts is valuable for roles like AWS Machine Learning specialists.

Is AWS Machine Learning a high paying job?

AWS Machine Learning roles are generally well-paid due to the specialized skills required, such as expertise in cloud computing, data science, and machine learning frameworks. Salaries vary based on experience, location, and certifications, but they tend to be higher than average for tech roles with similar responsibilities.

What are popular job titles related to Aws Machine Learning jobs in British Columbia?

For Aws Machine Learning jobs in British Columbia, the most frequently searched job titles are:

What job categories do people searching Aws Machine Learning jobs in British Columbia look for?

The top searched job categories for Aws Machine Learning jobs in British Columbia are:

Infographic showing various Aws Machine Learning job openings in British Columbia as of August 2026, with employment types broken down into 1% As Needed, 68% Full Time, 30% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $127,790 per year, or $61.4 per hour.

Head of Machine Learning - Aquaeye

BLANKSLATE Partners

Vancouver, BC

Full-time

Medical, Dental, Vision, PTO

Posted 7 days ago


Job description

AquaEye is a fast-growing company transforming the global water rescue industry by developing rapid-deployment, intelligent sonar solutions. Our flagship product, AquaEye, is a handheld sonar device with built-in AI detection to help first responders locate drowning victims faster and more effectively. As we continue to expand our global reach and develop new product lines, we are seeking a driven, hands-on Head of Machine Learning to own and advance innovation in our product's algorithms.

This role is central to AquaEye's core technology and strategic vision. The successful candidate will be responsible for leading ML strategy, overseeing end-to-end development, and solving some of our most challenging embedded ML problems.

Job Responsibilities

  • ML Strategy and Technical Direction
    • Define and execute our machine learning strategy aligned with evolving product and business objectives.
    • Lead the design and evolution of signal processing and machine learning architectures for production systems.
    • Establish technical standards, best practices, and development processes for ML systems.
    • Evaluate emerging machine learning technologies and identify opportunities to enhance product capabilities and competitive advantage.
    • Provide technical leadership on architecture decisions, model selection, and system performance optimization.
  • Machine Learning Platform & Model Development
    • Oversee the development, validation, deployment, and lifecycle management of machine learning models.
    • Oversee the design, optimization, and scalability of our signal processing pipelines.
    • Define model performance metrics and continuously drive improvements through rigorous evaluation and experimentation.
    • Ensure robustness, maintainability, and scalability of production ML infrastructure, data pipelines, and supporting databases.
    • Oversee ML Ops practices, including model versioning, reproducibility, monitoring, and continuous improvement.


  • Data Strategy & Dataset Governance
    • Establish standards for dataset acquisition, quality, governance, and lifecycle management.
    • Lead planning and execution of field data collection initiatives to ensure datasets meet product development and validation objectives.
    • Continually innovate on existing methodologies for data labeling, preprocessing, quality assurance, and representativeness across operational scenarios.
    • Oversee continuous expansion and refinement of training datasets to improve model accuracy and generalization.
  • Product Innovation & Cross-Functional Leadership
    • Work alongside Product Management, Engineering, and executive leadership to define the AI roadmap and prioritize development initiatives.
    • Translate customer needs and operational challenges into innovative machine learning solutions and product capabilities.
    • Provide technical leadership during customer demonstrations, field trials, and critical deployments.
    • Serve as the organization's subject matter expert for machine learning technologies, advising stakeholders on technical direction and product strategy.
  • Team Leadership & Organizational Development
    • Provide leadership and mentorship to develop a high performing machine learning team within the product development group.
    • Establish project priorities, resource allocation, and development plans to ensure successful delivery of strategic objectives.
    • Foster a culture of technical excellence, innovation, collaboration, and continuous learning.
    • Drive project execution through effective planning, risk management, and use of project management tools such as Jira.
    • Build organizational capability by defining engineering processes, conducting technical reviews, and promoting knowledge sharing across teams.

Requirements

Required Qualifications

  • Bachelor's or Master's degree in Engineering, Computer Science, Mathematics, Physics, or a related field
  • 5-10 years of experience in machine learning, AI, and software development
    • AWS
    • Claude
    • Writing in C - because its embedded
    • Python 
    • Scripting 
    • Converts algorithms to code and develops solutions that leverage machine learning concepts like decision trees, logistic regression, or Bayesian analysis to interpret large and complex data sets.
  • Proven track record of leading machine learning teams and delivering quality products
  • Experience with embedded ML on hardware / IoT devices
  • Experience translating real-world applications and customer needs into machine learning solutions
  • Strong proficiency in Python, with experience using PyTorch and Scikit-learn
  • End-to-end machine learning project experience, including data pipelines, 
  • data cleaning, preprocessing, model design, training, validation, and deployment
  • Experience with project management tools, including JIRA
  • Experience working with cloud platforms such as AWS or Azure
  • Strong technical communication, documentation, and organizational skills

Preferred Qualifications

  • Familiarity with sonar systems and sonar data
  • Familiarity with signal processing
  • Familiarity with computer vision such as object detection and Fourier transforms
  • Experience with IP strategy in AI innovation
  • Comfort in open water settings year-round (with appropriate PPE)

Benefits

What We Offer

As a company we aim to build innovative technology that puts people and their lives first. We apply the same approach to the way we run our company.  We aim to pay fairly compared to other organizations of similar size in Vancouver and we reward for growth, as we grow.

  • Salary range: $120,000 - $180,000
  • Competitive salary and performance-based incentives.
  • Employee ownership opportunities.
  • Health, dental, and vision coverage.
  • 4 weeks paid vacation plus company closure between Dec 24 - Jan 1.
  • Flexible and dynamic work environment.
  • Opportunity to directly impact the design and development of end product
  • Opportunity to work on a variety of tasks and be a part of the creation process of new products

DEI Statement: 

VodaSafe is a values-driven company that is deeply committed to building an equitable and diverse workforce.

We recognize that our greatest asset is our team. We encourage each team member to be their true, authentic selves. Curiosity, ambition, humility and empathy are at the base of everything we do. We welcome diverse perspectives, educational backgrounds and experiences in order to best serve our team, our customers and our community. 

Inclusion Statement: 

Hesitant to Apply? 

VodaSafe is an equal-opportunity employer. Throughout our hiring process, we make certain that all qualified applicants will receive consideration for employment without regard to race, ethnicity, religion, skin colour, sex, sexual orientation, gender identity, national origin, age, or disability. 

Research has shown that women and people of colour are less likely to apply for a position if they do not meet all of the qualifications listed in the job advertisement. At VodaSafe, we hire for potential. We recognize that no two journeys are the same - how you have gained and collected your skillset is unique to your experiences. We want to encourage you to apply even if all criteria on the job posting are not met.Â