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Founding Machine Learning Engineer Jobs in Burnaby, BC

About the Role As a Machine Learning Engineer in Agent Factory, you'll design and build the core ML systems behind Workday's next generation of AI agents. Working within a small, senior, cross ...

We are currently seeking a Manager, Machine Learning Engineering to join our rapidly growing engineering organization. This role is for someone who is passionate about building innovative solutions ...

Work with interdisciplinary teams of developers, designers, and business experts to develop ... Machine Learning engineering practices. You will act as a technical partner and lead by example ...

We're forming small, senior, cross-functional AI teams that bring together product leaders, machine learning engineers, and full-stack builders to create intelligent agents used by millions of people ...

The Founding Engineering team will work remotely through the summer. Starting September 1, the role ... Lead complex, cross-functional programs spanning Data Engineering, Machine Learning, Science, and ...

The Founding Engineering team will work remotely through the summer. Starting September 1, the role ... Lead complex, cross-functional programs spanning Data Engineering, Machine Learning, Science, and ...

Showing results 21-40

Founding Machine Learning Engineer information

What is a founding machine learning engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.

What are some unique challenges and expectations for a founding machine learning engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

What are the key skills and qualifications needed to thrive as a founding machine learning engineer, and why are they important?

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.

Are founding machine learning engineers still in demand?

Founding machine learning engineers remain in high demand as companies seek to develop AI-driven products and services. They often require strong skills in deep learning, data modeling, and proficiency with tools like TensorFlow or PyTorch, with demand driven by growth in AI applications across industries.

How much does a founding machine learning engineer make?

A founding machine learning engineer typically earns between $100,000 and $180,000 annually, depending on experience, location, and company size. Equity and bonuses may also be part of the compensation package, especially in startup environments where they play a significant role in total earnings.

What are popular job titles related to Founding Machine Learning Engineer jobs in Burnaby, BC?

For Founding Machine Learning Engineer jobs in Burnaby, BC, the most frequently searched job titles are:

Head of Machine Learning - Aquaeye

BLANKSLATE Partners

Vancouver, BC

Full-time

Medical, Dental, Vision, PTO

Posted 5 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