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At Ontario Health we are committed to developing a strong organizational culture that connects and inspires all team members across the province. Our vision is that together we will be a leader in health and wellness for all. Our mission is to connect the health system to drive improved and equitable health outcomes experiences and value. How we work together is reflected through our five values: integrity inspiration tenacity humility and care.
What Ontario Health offers:
Achieving your career goals is a priority to us. Benefits of working at Ontario Health may include the following based on employment type:
Fully paid medical dental and vision coverage from your first day
a health care spending or wellness spending account
a premium defined benefit pension plan
three personal days and two float days annually
three weeks vacation to start (for individual contributors) increasing to four weeks after two years
career development opportunities
a collaborative valuesbased team culture
a wellness program
a hybrid working model
participation in Communities of Inclusion
Want to make a difference in your career Consider this opportunity.
As an NLP Developer Intern you will work on developing and deploying endtoend NLP pipelines on cloud for healthcare applications. You will gain handson experience with building machine learning pipelines and working with Azure ML Studio and/or Amazon SageMaker to operationalize your solutions in a realworld healthcare environment.
Here is what you will be doing:
Collaborate with data scientists and healthcare professionals to define problem statements model objectives and deliverables.
Build and optimize endtoend machine learning pipelines including data ingestion feature engineering model training evaluation and deployment on Major cloud services (Azure AWS).
Use (Azure AWS) services to create robust scalable ML pipelines.
Collaborate with DevOps teams to implement CI/CD workflows.
Implement monitoring tools to track model performance and data drift (e.g MLflow W&B etc.
Document your work including code processes and lessons learned for knowledge sharing with the broader team.
Here is what you will need to be successful:
Education:
Currently pursuing a Masters or Ph.D. degree in Computer Science Data Science Engineering or a related field.
Knowledge & Skills:
Strong programming skills in Python and experience with NLP libraries (e.g. SpaCy Hugging Face NLTK).
Familiarity with Azure/AWS python SDK and machine learning frameworks such as PyTorch and Scikitlearn.
Experience and interest in working with Azure ML Studio Amazon SageMaker and other (Azure AWS) services.
Working knowledge of SQL and pandas for data manipulation.
Experience with version control (Git) and MLOps practices.
Strong problemsolving and communication skills with the ability to work collaboratively in a team.
Experience with using deep learning techniques and NLP models such as transformers (BERT GPT etc.
Familiarity with healthcare data and compliance standards is a plus.
What You Will Gain:
Handson MLOps experience developing NLP pipelines in a realworld healthcare setting.
Exposure to Cloud Services for building and deploying endtoend machine learning solutions.
Experience working on impactful projects that help drive better healthcare outcomes for Ontario population.
Location: Toronto Ontario (currently hybrid; subject to change)
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Employment Type:
Student Paid (Fixed Term) Full timeContract Length:
4 Month(s)Salary Band:
StudentExternal Application Deadline Date:
April 15 2025All applicants must be a resident of Ontario to be considered for roles at Ontario Health.
Ontario Health encourages applications from candidates who are First Nations Mtis Inuit and urban Indigenous; Francophone; members ofBlack and racializedgroups; 2SLGBTQIA communities; trans and nonbinary individuals;and people living with disabilities.
Ontario Health is an accessible employer and we offer accommodation in all aspects of employment including the recruitment process. If you require a disability related accommodation in order to participate in the recruitment process please email and a member of the team will connect with you within 48 hours.
Required Experience:
Intern
Full-Time