Machine Learning Engineer

Empire Life
Canada
130 $-160 $ / jour (estimé)
Temps plein

Please note the base salary will be determined by the successful candidate's education, skills and experience. The listed salary range serves as a general pay guideline for this position's pay level.

Machine Learning Engineer

Location : Remote - Anywhere in Canada

Empire life is looking to hire a Machine Learning Engineer to join our Data Science team! The Machine Learning Engineer plays a pivotal role in integrating Machine Learning (ML) models and Generative AI (GenAI) solutions into complex systems and applications.

Your expertise in AI technologies, machine learning models, and software engineering is crucial for designing and implementing seamless integrations that enhance the performance and functionality of AI and ML-driven solutions.

Proficiency in integrating Generative AI technologies and ML models is essential for harnessing the power of intelligent automation, natural language processing, and cognitive computing.

The Machine Learning Engineer will assist in the development and deployment of advanced analytics solutions supporting various business units.

Why pursue this opportunity

  • The role - this is a new position and your chance to join a growing team, while being provided the opportunity to make an impact.
  • Play an integral role - this is an opportunity that allows for you to grow your skills, while directly contributing to the business unit you are a part of.
  • Diversity, equity, and inclusion - we are committed to creating a diverse, equitable, and inclusive workplace and welcome candidates who share this commitment.

What you’ll be working on

  • Collaborate with data scientists, data analysts and software engineers to understand AI / ML models and design integration strategies that align with business requirements.
  • Building AI / ML pipelines : Design, implement, and optimize end-to-end AI and machine learning pipelines for data ingestion, preprocessing, modeling, and deployment, ensuring efficiency and scalability.
  • Feature engineering : Translate features developed by data scientists during model development and implement the feature functionality in the AI / ML application to enhance model performance and improve predictive accuracy.
  • Model deployment : Deploy AI / ML models into production environments, ensuring reliability, scalability, and seamless integration with existing systems.
  • Testing and validation : Develop and execute testing and validation procedures to verify the accuracy, robustness, and reliability of AI / ML models and data processing pipelines.
  • Ensure the reliability, and scalability of AI / ML applications in production environments including ML pipelines and Generative AI solutions.
  • Work with DevSecOps and infrastructure teams to automate deployment, monitoring, and scaling of integrated AI and ML solutions.

What we’re looking for you to have

  • University degree or higher in Computer Science, with a concentration in data science and machine learning programming and techniques preferred
  • 2-3 years of working experience in a in a technical role within the financial or insurance fields
  • Strong programming skills in Python, SQL
  • Proficient in Git and CI / CD automation ie Github Actions, Terraform
  • Deep understanding of machine-learning concepts and algorithms (Random Forests, XGBoost, Neural Networks etc.)
  • Strong understanding of cloud platforms (e.g. Azure, GCP) for deploying and managing integrated Gen AI and ML solutions
  • Experience with containerization and orchestration technologies such as Kubernetes and Docker
  • Knowledge of event-driven architectures, message broker systems (eg Pub / Sub, Kafka), and real-time data processing technologies with a focus on dealing with unstructured data for Gen AI use cases.
  • Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes) for packaging and deploying Gen AI applications.
  • Intellectual curiosity and creativity
  • Good communications and collaboration skills
  • Ability to work independently and as a member of a team
  • If you are applying for a position which is open to applicants across Canada, unless otherwise indicated in the position, language proficiency in English is required for communicating with customers, advisors, or employees across Canada.

Beyond the salary

For regular full-time positions, Empire Life offers a comprehensive total rewards package that includes :

  • Competitive salaries with annual pay increases
  • Annual bonus program, which recognizes both strong company performance and individual contributions, for non sales positions
  • Competitive uncapped commission, for sales positions
  • A comprehensive employer-funded benefits package that includes life insurance, disability, health and dental and a generous health account
  • Flexible work arrangements and an annual allotment of personal health days.
  • Four weeks annual vacation from hire date
  • A defined contribution pension plan with generous employer matching
  • Top up programs for parental leave and compassionate leave
  • Employer-sponsored wellness and recognition programs
  • A cash employee referral program

To learn more about working at Empire Life, visit https : / / www.empire.ca / workatempire .

Get to know us

Empire life is proud to be an equal opportunity employer. We celebrate diversity, are committed to creating an inclusive environment, and welcome everyone to participate in our application process.

We encourage those of all backgrounds and experiences to apply, even if you don't believe you meet each unique qualification outlined.

Applicants will receive equal consideration without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, or age.

Empire Life welcomes applications from people with disabilities and disabled people. Accommodations are available upon request for candidates taking part in all aspects of the screening and selection process.

If you need this job posting in an alternative format or have any accessibility questions, please contact [email protected]

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