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ML Deployment Engineer - SickKids AI (SKAI) Service

SickKids
Toronto, ON

Postuler dès maintenant

Détails du poste

Contrat à durée déterminée

Avantages

Assurance Dentaire
Assurance Vie

Compétences

CI/CD
Informatique
Azure
Informatique
Kubernetes
Ansible
Bases de données relationnelles
DevOps
Ingénierie
Git
Docker
Baccalauréat
PostgreSQL
Systèmes distribués
Terraform
Ingénierie des systèmes
GitHub
Linux
GitLab
Compétences en communication
Python
Shell scripting
Débogage
MySQL
Gestion du temps

Description complète du poste

About SickKids

Dedicated exclusively to children and their families, The Hospital for Sick Children (SickKids) is one of the largest and most respected paediatric healthcare centres in the world. As innovators in child health, we lead and partner to improve the health of children through the integration of healthcare, leading-edge research and education. Our reputation would not have been built - nor could it be maintained - without the skills, knowledge and experience of the extraordinary people who come to work here every day. SickKids is committed to ongoing learning and development, and features a caring and supportive work environment that combines exceptionally high standards of practice.

When you join SickKids, you become part of our community. We share a commitment and determination to fulfill our vision of Healthier Children. A Better World.

Don't miss out on the opportunity to work alongside the world's best in paediatric healthcare.

Position Description

SickKids AI is leading a transformative enterprise-wide program to deliver leading edge, data-driven, individualized paediatric health care and operations through AI. Known as SickKids AI Service, or SKAI Service, our team delivers end-to-end AI and machine learning (ML) solutions to high-impact clinical and operational challenges. With a keen focus on sustainable and responsible deployment, you will partner with SickKids' experts to design, build, and maintain the systems infrastructure that powers world-leading AI and ML solutions across all areas of clinical care and hospital operations, enabling us to realize SickKids' vision of Healthier Children. A Better World.

As a ML Deployment Engineer on the SKAI team, you will sit at the intersection of infrastructure and AI/ML engineering, bridging the gap between model development and production. You will be responsible for the reliable operation of our hybrid on-premises and cloud environments, while also contributing hands-on to the productionization and lifecycle management of AI/ML models and data pipelines.

Here's What You'll Get to Do

Design, deploy, and maintain hybrid infrastructure spanning on-premises servers and cloud services
Productionize AI/ML models developed by data scientists, building robust, scalable, and monitored deployment pipelines
Build and maintain CI/CD (Continuous Integration / Continuous Deployment) pipelines for automated testing, integration, and deployment of AI/ML systems and infrastructure-as-code
Manage and maintain containerized workloads using Docker and related orchestration tooling
Administer and optimize relational databases (such as MariaDB) and data lake environments to support AI/ML workflows
Develop and maintain data pipelines that move and transform data across on-prem and cloud environments
Monitor deployed AI/ML systems in production, ensuring reliability, performance, and observability
Collaborate closely with data scientists and software engineers to accelerate the path from prototype to production
Contribute to version control best practices and repository management using Git
Identify and resolve infrastructure bottlenecks, system failures, and performance issues across the stack
Work with some of the best clinicians, data scientists, and software engineers in the world

Here's What You'll Need

Background in computer science, systems engineering, or a related field with:
Bachelor's degree or equivalent with a minimum of 3 years of relevant experience, OR
Diploma or college certification with a minimum of 5 years of relevant hands-on experience
Demonstrated experience managing and operating both on premises Linux server environments and cloud services
Proficiency in Python and shell scripting for automation and systems tooling
Hands-on experience with Docker and containerization, including building, deploying, and troubleshooting containerized applications
Experience designing and maintaining CI/CD pipelines (e.g., Azure DevOps, GitHub Actions, GitLab CI, or similar)
Proficiency with Git for version control and collaborative development workflows
Experience administering relational databases, with exposure to MariaDB or similar (MySQL, PostgreSQL)
Familiarity with data lake concepts and technologies, including structured and unstructured data storage at scale
Understanding of ML model lifecycle management, including model serving, versioning, and monitoring in production
Excellent problem-solving skills and a systematic approach to debugging complex, distributed systems
Strong verbal and written communication skills with the ability to work collaboratively across technical and clinical stakeholders
Excellent project and time management skills with strong attention to detail
Demonstrated commitment to advancing equity, diversity, and inclusion objectives

This Will Make You Extra Competitive

Experience working in a healthcare or regulated environment with strict data governance and security requirements
Familiarity with MLflow or similar ML experiment tracking and model registry platforms
Experience with Azure-specific services such as Azure Machine Learning, Azure Data Factory, Azure Blob Storage, and Azure Kubernetes Service (AKS), or equivalent from another cloud provider
Knowledge of infrastructure-as-code tools (e.g., Terraform, Bicep, Ansible)
Exposure to data engineering practices, including ETL/ELT (Extract, Transform, Load / Extract, Load, Transform) pipeline development
Familiarity with monitoring and observability tooling (e.g., Prometheus, Grafana, Azure Monitor)
Experience with Electronic Health Record (EHR) data or other clinical data systems

Some Exciting Benefits of Working at SickKids

This position is eligible for employee benefits coverage including but not limited to; health, dental and life insurance. The full benefits package will be discussed at the time of offer.
A focus on employee wellness with our new Staff Health and Well-being Strategy. Self-care helps us support others.
A hospital that welcomes and focuses on Equity, Diversity, and Inclusion.
The opportunity to make an impact. Regardless of your role or professional interest, you will be making a difference at SickKids and contributing to our vision of Healthier Children. A Better World.
For more on why you'll love working at SickKids, visit our careers site.

Employment type: Hybrid 1-year Contract (with renewal option)

Our Commitment to Diversity

SickKids is committed to championing equity, diversity and inclusion in all that we do, fostering an intentionally inclusive and culturally safe environment that reflects the diversity of the patients, families and communities we serve. Learn more about workplace inclusion.

Accessibility & Accommodation

If you require accommodation during the application process, please reach out to our aSKHR team. SickKids can provide access and inclusion supports to eligible candidates to support their full engagement during the interview and selection process as well as to ensure candidates are able to perform their duties once successfully hired. If you are invited for an interview and require accommodation, please let us know at the time of your invitation to interview. Information received related to access, inclusion or accommodation will be addressed confidentially.

How To Apply

Technical difficulties? Email [email protected] with a short description of the issues you are experiencing. We will not accept resumes sent to this inbox but we are happy to respond to requests for technical assistance.

Tip: Combine your cover letter and resume into ONE document of 20 pages or less as you cannot upload multiple documents as part of your application.

Every application is reviewed by a human recruiter and all hiring decisions are made by people. In some cases, AI-assisted tools are used to help review applications based on job-related qualifications.

All positions posted on the SickKids Hospital's Careers Site represent current vacancies, unless otherwise posted in the job description.

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