ML Platform Engineering Team – DevOps engineer
Deploy and modernize ML infrastructure on Kubernetes, ensuring secure, scalable systems for data processing, model training, and prediction serving using Azure, Docker, Terraform, and Helm.
- Compensation
- CA$65–CA$75 / hr
- Location
- Toronto, Canada
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Part time
- Experience
- 7+ years
- Category
- Devops
- Posted
Skills
Must have
- 7+ years of experience building sophisticated and automated production infrastructure
- Experience with Kubernetes, docker and container orchestration
- Experience with Terraform
- A background in software engineering, working within a software development team
- Solid cloud experience (Preferably Azure or AWS)
- Experience with managing CI/CD tools and pipelines
- Experience with Linux systems administration skills in a Cloud environment, Redhat and Ubuntu
- Experience with Git, and Jenkins
- Strong verbal and written communication skills, with the ability to work effectively across teams and produce engineering documentation
- BA/BS degree or equivalent experience; Computer Science background preferred
Nice to have
- Knowledge of IP networking, VPN’s, DNS, load balancing and firewalls
- Familiarity with monitoring tools
- Experience with automated testing tools
- Experience troubleshooting and tuning systems performance
- Experience with Saltstack or other configuration management
- Experience resolving and triaging docker image problems
- Experience optimizing system-level design and architecture
Full description
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Direct message the job poster from Themesoft Inc.
Themesoft Inc. is a global IT solutions provider and a Woman‑Owned Minority Business Enterprise headquartered in Dallas, TX. With a strong presence across the US, Canada, India, Singapore, and Brazil, we specialize in digital transformation, consulting, and workforce solutions across diverse industries.
We are currently looking for a tech-savvy and results-driven professional for one of our leading clients. If you’re passionate about technology and looking to grow in a dynamic, fast-paced environment, this could be the perfect fit for you!
6+ months Contract with Potential Extention
Potential updated:
You will be deploying and modernizing Machine Learning Kubernetes infrastructure. Ensuring deployments comply with enterprise security standards. The day-to-day task involves delivery, deployment, and upgrading of scalable systems designed for data ingestion, processing, validation, model training, large-scale computation, monitoring, and serving prediction results.
Our stack for DevOps includes: Kubernetes, Docker, Databricks, Blobfuse, Terraform, Helm, Github Actions, and Saltstack, with a majority of our infrastructure running on Azure cloud.
Job Requirements
Must-Have:
- 7+ years of experience building sophisticated and automated production infrastructure
- Experience with Kubernetes, docker and container orchestration
- Experience with Terraform
- A background in software engineering, working within a software development team
- Solid cloud experience (Preferably Azure or AWS)
- Experience with managing CI/CD tools and pipelines
- Experience with Linux systems administration skills in a Cloud environment, Redhat and Ubuntu
- Experience with Git, and Jenkins
- Strong verbal and written communication skills, with the ability to work effectively across teams and produce engineering documentation
- BA/BS degree or equivalent experience; Computer Science background preferred
Nice-to-Have:
- Knowledge of IP networking, VPN’s, DNS, load balancing and firewalls
- Familiarity with monitoring tools
- Experience with automated testing tools
- Experience troubleshooting and tuning systems performance
- Experience with Saltstack or other configuration management
- Experience resolving and triaging docker image problems
- Experience optimizing system-level design and architecture