Software Engineer delivering MLOps solutions for Generative AI at DataGalaxy. Focusing on reliability and collaboration with product engineering teams in a hybrid environment.
About the role
- Associate Machine Learning Developer responsible for delivering ML solutions to public sector partners. Gain hands-on experience for professional success during a 4-month internship period.
Responsibilities
- Participate in team planning sessions and educational presentations
- Review the data to understand its overall scope and structure
- Identifying the right metric to measure the success of the model and project
- Work in teams to pre-process the data for analysis and model development
- Uncover trends, insights, and key features to help guide where ML solutions can be applied
- Develop models around the available data and suggested set of problems
- For viable use cases develop proof of concept working models
- Suggest and explore novel solutions to a problem and detailed recommendations for how to integrate the models in business
- Communicating and presenting your teams work to AltaML and Public Sector Partners
- Get familiarity with various data processing tools and exposure to AI/ML algorithms
- Independently researching and connecting with your cohort to gain domain knowledge and learn state-of-the-art techniques.
Requirements
- Enrolled in a Post secondary degree program at U of Alberta, U of Calgary (Masters Only), U Waterloo, or U of Toronto for the duration of the internship term
- General knowledge of and experience developing in Python and data science libraries/packages such as pandas, scikit-learn, matplotlib
- Understanding of Machine Learning and software development concepts
- Must be able to work 40 hours per week during the internship
- Must have a valid citizenship and/or work permit that legally allows you to work full-time during the internship term.
- Nice to have:
- Exposure to version control/Git
- Experience with a cloud platform such as Azure, AWS or GCP
- Ability to work independently and within a team environment
- Well-developed communication skills, with the ability to engage in client meetings and deliver professional presentations.
Benefits
- This opportunity is funded in partnership with Mitacs.
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Senior Machine Learning Engineer responsible for designing, building, and deploying ML solutions. Joining a global tech group tackling high - impact projects in Buenos Aires.
Principal Machine Learning Engineer at Qodea responsible for leading ML model lifecycle and collaborating on AI solutions in Buenos Aires delivery center.
Lead ML Ops Engineer for a fast - growing AI startup focused on scalable infrastructure. Drive hands - on execution across the entire model lifecycle in a collaborative environment.
Lead Machine Learning Engineer creating personalized item recommendations for Target.com and the Target App. Designing and optimizing production ML solutions with a team of data scientists and engineers.
Senior Machine Learning Engineer at Doctrine focusing on developing NLP models for legal document processing. Join an ambitious team to innovate within the field of legal technology.
MLOps Engineer responsible for designing and maintaining ML pipelines at JobCloud. Collaborating with teams to productionize ML models and ensuring robust system performance.
Senior ML Engineer developing scalable production ML systems across various teams in JobCloud. Leading innovation in the AI - driven recruitment landscape, improving job ad visibility and performance.
Senior Machine Learning Engineer at greehill developing ML solutions for sustainable urban living. Leading projects in Computer Vision and Deep Learning to transform urban environments.
Machine Learning Engineer developing deep learning models for self - driving vehicle systems at BlueSpace.ai. Engage in innovative ML applications while collaborating with a seasoned team in the autonomous vehicle ecosystem.