Senior Machine Learning Engineer - MLOps & Platform Engineering (34107)
About the role
We’re currently seeking a seasoned Machine Learning Engineer who thrives at the intersection of data science, engineering, and operations. This role is ideal for someone who has not only mastered the craft of building and scaling ML solutions, but also knows how to put them into production, and keep them running smoothly.
What You’ll Be Doing The role is a mix of MLOps, platform development, and hands-on model engineering. You’ll be responsible for designing automated workflows that take ML models from development to deployment with minimal friction. This includes developing robust CI/CD pipelines (preferably using Azure DevOps or GitHub Actions) and managing model lifecycle tasks such as versioning, monitoring, and retraining.
A large portion of your time will be spent working within Databricks—developing feature pipelines, optimizing model workflows, and integrating ML components with existing SaaS systems. You’ll also help migrate and scale models within an environment already hosting over 100 ML models, with another 25+ targeted for transition.
On the application side, you’ll work closely with data scientists to productionalize machine learning prototypes. You’ll select appropriate algorithms, build scalable ML systems using Python-based frameworks like TensorFlow and PyTorch, and help tune and evaluate performance over time.
The Ideal Candidate Brings
- 5+ years of experience in software, data, or DevOps engineering roles—with at least 3 of those focused on MLOps or ML engineering.
- Expertise in Python, and confidence working with key ML frameworks (TensorFlow, PyTorch, scikit-learn).
- Hands-on experience working in the Microsoft Azure ecosystem—particularly Azure ML, AKS, and Azure DevOps.
- Deep familiarity with Databricks (including Delta Lake, MLflow, and Apache Spark) is non-negotiable.
- An understanding of infrastructure-as-code (e.g., Terraform), version control, and CI/CD practices in ML workflows.
- Strong communication skills and the ability to work cross-functionally across technical and business teams.
- You must be located in Canada and able to work with Canadian teams.
Additional
- Certifications from Databricks or Microsoft (e.g., Azure Solution Architect).
- Experience working with LLM libraries or frameworks like transformers, trl, or deepspeed.
- Prior involvement in ML model migration projects or SaaS ML platform integration.
- A consulting background or client-facing role where clear communication and stakeholder management were key.
, : Matheo Theodossiou
About Myticas Consulting
Myticas Consulting is a proven industry-leading IT Staffing and Recruitment organization, with active locations in major North American cities such as Ottawa Ontario, Chicago Illinois, and Atlanta Georgia.
Our large team of IT recruitment and sales professionals have over 50+ years of combined experience providing the highest quality of Telecommunication Engineering, ERP and IT Software Development resources, to both Public and Private sector enterprise level environments.
Here at Myticas, we strive to continually provide unmatched quality of IT resources, that prove to stand the test of time, and go above and beyond all project expectations and deliverables.
The "motto" at Myticas is not only to work with you, but to understand what success really looks like for your organization, and to deliver the IT staffing needs that matter most to increasing both the functionality and efficiency of your environment.
With our evolving expertise in Telecom, ERP, DW/BI and EAI resources, and a guaranteed replacement program for all our partners, the defined win-win scenario has never been presented in a more simple manner.
Senior Machine Learning Engineer - MLOps & Platform Engineering (34107)
About the role
We’re currently seeking a seasoned Machine Learning Engineer who thrives at the intersection of data science, engineering, and operations. This role is ideal for someone who has not only mastered the craft of building and scaling ML solutions, but also knows how to put them into production, and keep them running smoothly.
What You’ll Be Doing The role is a mix of MLOps, platform development, and hands-on model engineering. You’ll be responsible for designing automated workflows that take ML models from development to deployment with minimal friction. This includes developing robust CI/CD pipelines (preferably using Azure DevOps or GitHub Actions) and managing model lifecycle tasks such as versioning, monitoring, and retraining.
A large portion of your time will be spent working within Databricks—developing feature pipelines, optimizing model workflows, and integrating ML components with existing SaaS systems. You’ll also help migrate and scale models within an environment already hosting over 100 ML models, with another 25+ targeted for transition.
On the application side, you’ll work closely with data scientists to productionalize machine learning prototypes. You’ll select appropriate algorithms, build scalable ML systems using Python-based frameworks like TensorFlow and PyTorch, and help tune and evaluate performance over time.
The Ideal Candidate Brings
- 5+ years of experience in software, data, or DevOps engineering roles—with at least 3 of those focused on MLOps or ML engineering.
- Expertise in Python, and confidence working with key ML frameworks (TensorFlow, PyTorch, scikit-learn).
- Hands-on experience working in the Microsoft Azure ecosystem—particularly Azure ML, AKS, and Azure DevOps.
- Deep familiarity with Databricks (including Delta Lake, MLflow, and Apache Spark) is non-negotiable.
- An understanding of infrastructure-as-code (e.g., Terraform), version control, and CI/CD practices in ML workflows.
- Strong communication skills and the ability to work cross-functionally across technical and business teams.
- You must be located in Canada and able to work with Canadian teams.
Additional
- Certifications from Databricks or Microsoft (e.g., Azure Solution Architect).
- Experience working with LLM libraries or frameworks like transformers, trl, or deepspeed.
- Prior involvement in ML model migration projects or SaaS ML platform integration.
- A consulting background or client-facing role where clear communication and stakeholder management were key.
, : Matheo Theodossiou
About Myticas Consulting
Myticas Consulting is a proven industry-leading IT Staffing and Recruitment organization, with active locations in major North American cities such as Ottawa Ontario, Chicago Illinois, and Atlanta Georgia.
Our large team of IT recruitment and sales professionals have over 50+ years of combined experience providing the highest quality of Telecommunication Engineering, ERP and IT Software Development resources, to both Public and Private sector enterprise level environments.
Here at Myticas, we strive to continually provide unmatched quality of IT resources, that prove to stand the test of time, and go above and beyond all project expectations and deliverables.
The "motto" at Myticas is not only to work with you, but to understand what success really looks like for your organization, and to deliver the IT staffing needs that matter most to increasing both the functionality and efficiency of your environment.
With our evolving expertise in Telecom, ERP, DW/BI and EAI resources, and a guaranteed replacement program for all our partners, the defined win-win scenario has never been presented in a more simple manner.