Machine Learning Engineer II

1 month ago

Ottawa, Canada Gentex Corporation Full time
POSITION OVERVIEW

Machine Learning Engineer II will research, design, develop, and deploy machine learning models and algorithms that enhance our products and drive business value. They will collaborate with cross-functional teams, including systems engineers, software engineers, and product managers, to implement scalable and efficient machine learning solutions.

WHAT YOU’LL DO

  • Design, build, and optimize machine learning models for various applications, including classification, detection, regression, and clustering tasks.
  • Collect data through experiment design and setup.
  • Process and analyze large datasets, ensuring data quality and integrity for effective model training.
  • Evaluate and implement suitable machine learning algorithms based on project requirements and performance metrics.
  • Work closely with product and software teams to translate requirements into technical solutions, providing insights and recommendations throughout the development process.
  • Deploy machine learning models onto hardware, ensuring scalability, reliability, and performance.
  • Continuously monitor model performance and implement updates or improvements as needed based on feedback and changing requirements.
  • Maintain clear documentation of models, processes, and best practices to facilitate knowledge sharing within the team.
  • Stay current with industry trends and advancements in machine learning and AI, contributing innovative ideas to enhance our capabilities.
  • Other duties as assigned.

HOW YOU’LL DO IT

  • Optimizing work processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.
  • Quality Focus - Promoting and maintaining high standards of work, looking for ways to improve products and services, while encouraging coworkers to do so as well.
  • Planning and aligning - Planning and prioritizing work to meet commitments aligned with organizational goals.
  • Fostering Teamwork - Building effective partnerships and working collaboratively with others to meet shared objectives. Interface with other departments on the production teams’ behalf to ensure that the company quality standards and customer requirements are met.  
  • Cultivating innovation - Creating new and better ways for the organization to be successful. 
  • Maintaining a high level of honesty, integrity, and confidentiality with respect to company matters.
  • Complying with all Company policies and procedures, safety regulations, company safety policies and safely perform all duties , including but not limited to, promoting a safe workplace.   
     

WHAT TO BRING

  • Bachelor’s degree in Engineering, Computer Science, Data Science, Mathematics, or a related field.
  • 3+ years of professional experience in machine learning or data science roles, with a proven track record of developing and deploying machine learning models.
  • Proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Familiarity with data processing frameworks (e.g., Pandas, NumPy).
  • Knowledge of cloud platforms (e.g., AWS, Google Cloud, Azure).
  • Experience building end-to-end machine learning workflows including data collection, grading, model training, evaluation, deployment, and performance monitoring.
  • Proficiency in Microsoft Office Suite.

WHAT WILL HELP

  • Professional experience in a complimentary field such as software development.
  • Master’s degree in a quantitative field such as Computer Science, Electrical Engineering, Mathematics, or related technical field.
  • Strong problem-solving skills with the ability to analyze complex data and derive actionable insights.
  • Excellent verbal and written communication skills, with the ability to convey technical concepts to non-technical stakeholders.
  • Knowledge of containerization (e.g., Docker, Podman, Kubernetes).
  • Experience with embedded systems architecture and design.
  • Ability to work collaboratively in a team-oriented environment and manage multiple priorities effectively.
  • Ability to quickly comprehend and apply new technologies.

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