Overview
Machine Learning Engineer Jobs in Sandyville at Empire Life
Title: Machine Learning Engineer
Company: Empire Life
Location: Sandyville
Category: IT/Tech, Software Development
Location: Sandyville
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 Dev Sec Ops 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 preferred2-3 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 …
