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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and deploying machine learning models and generative AI use cases, with a strong focus on model training, feature engineering, and collaboration with cross-functional teams. Proficient in cloud technologies and DevOps practices to ensure scalable and high-quality deliverables.
Highest-signal resume keywords
Machine Learning Model DevelopmentGenerative AI Use Case DevelopmentDeep Learning Frameworks (TensorFlow, PyTorch)Cloud Expertise (Azure, AWS, GCP)DevOps Tools (GitHub, Jenkins, Ansible)
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Programming Languages (Java, Python, Shell Script)ML Model PipelinesFeature EngineeringModel TrainingLLM Models (Cohere, Haiku)Application Monitoring Tools (Dynatrace, Prognosis)ELK Technology StackGraph Databases (Neo4j, Neptune)Modern UI Technologies (React, Angular)Cloud Technologies (OpenShift, Docker, Kubernetes)
Soft Skills
MentoringCollaborationTechnical InfluenceKnowledge SharingInnovative Thinking
Tools & Technologies
GitHubJenkinsUrban CodeNexusAnsibleDynatracePrognosisTensorFlowPyTorchDocker
Industry Keywords
Machine LearningGenerative AIDeep LearningCloud ComputingDevOps
Tech Stack
Tools & technologiesAngularAnsibleAWSAzureCloudDockerGoogle Cloud PlatformJavaJenkinsKubernetesNeo4jOpenShiftPythonPyTorchReactTensorflow
About the role
Key responsibilities & impact- Design, code, and deploy machine learning models and generative AI use cases
- Enhance machine learning use-case development, model training, and feature-engineering pipelines
- Develop new generative AI use cases and enhance existing solutions
- Partner with the Data Analytics team to translate business requirements into technical solutions
- Provide technical influence by sharing knowledge, mentoring team members, and establishing best practices
- Ensure code quality, best practices, and scalability across deliverables
- Research emerging trends and industry best practices and evaluate implications for business strategy
Requirements
What you’ll need- Strong proficiency in programming and scripting languages (Java, Python, Shell Script, etc.)
- Hands-on experience developing and managing ML model pipelines, feature engineering, model training, and inferencing
- Proven experience with LLM models (Cohere, Haiku, and other cognitive services) in production environments
- Deep expertise in deep learning frameworks (TensorFlow, PyTorch)
- Ability to work effectively with cross-functional teams to understand product usage and generate innovative ideas
- Experience with application monitoring tools (Dynatrace, Prognosis)
- Solid knowledge of DevOps tools and practices (GitHub, Jenkins, Urban Code, Nexus, Ansible)
- Public and Private cloud expertise (Azure, AWS, GCP, OpenShift, Docker, Kubernetes)
- Experience with ELK technology stack and graph databases (Neo4j, Neptune) (nice to have)
- Some experience with modern UI technologies (React, Angular) (nice to have)
Benefits
Comp & perks- Leaders who support your development through coaching and learning opportunities
- Work in a dynamic, collaborative, progressive and highly performing team
- Ability to make a difference and lasting impact
- Network and build lasting relationships with students from diverse backgrounds from across Canada