Remote opportunity at
ClaritiSenior MLOps Engineer
Clariti seeks a Senior MLOps Engineer to join its team on a remote basis. As the inaugural MLOps specialist at the organization, the person in this…
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About This Role
Clariti seeks a Senior MLOps Engineer to join its team on a remote basis. As the inaugural MLOps specialist at the organization, the person in this role will design, build, and scale the infrastructure supporting AI capabilities for CivCheck and Clariti. The work focuses on streamlining the movement of machine learning models from the research phase into production environments with an emphasis on reliability, performance, and observability. This position suits…
Job Description
Clariti seeks a Senior MLOps Engineer to join its team on a remote basis. As the inaugural MLOps specialist at the organization, the person in this role will design, build, and scale the infrastructure supporting AI capabilities for CivCheck and Clariti. The work focuses on streamlining the movement of machine learning models from the research phase into production environments with an emphasis on reliability, performance, and observability. This position suits individuals who operate comfortably at the intersection of cloud infrastructure, machine learning, and software engineering, and who want to empower teams to deliver impactful ML systems securely and efficiently.
Clariti provides software solutions designed to assist governments and municipalities in managing building code compliance, permitting, and plan reviews. Its Guided AI Plan Review platform combines human expertise with intelligent automation to help communities navigate complex building regulations.
Responsibilities
- Design and maintain end-to-end machine learning pipelines for model training, evaluation, and deployment, including agentic AI workflows
- Build and optimize infrastructure for model serving and training across compute instances and cloud providers
- Develop tools dedicated to data pipelines, automated retraining, data labeling, and experiment performance tracking
- Partner with AI researchers and machine learning engineers to productionize proofs of concept while guaranteeing model scalability and reproducibility
- Implement continuous integration, automated testing, and deployment workflows adhering to ML CI/CD best practices
- Manage and monitor production model health, data quality, performance, and drift
- Collaborate with engineering teams to optimize data access and streamline infrastructure provisioning
- Drive performance tuning and cost optimization for large-scale model training
- Create internal documentation and establish best practices
Requirements
- Between 6 and 10+ years of total experience in software or machine learning engineering
- At least 3 years of focused experience in MLOps or machine learning infrastructure
- Solid working knowledge of programming languages including Python, C, C++, and Bash
- Demonstrated background in deploying and maintaining production machine learning models
- Proficiency with Kubernetes and Docker for scalable machine learning system architecture
- Practical experience utilizing major cloud platforms such as AWS, GCP, or Azure alongside GPU orchestration
- Hands-on familiarity with CI/CD tools like GitHub Actions or Jenkins
- Experience using tracking and automation tools such as MLflow, Kubeflow, and Weights & Biases
- Understanding of data versioning, monitoring strategies, and model reproducibility
Qualifications
- Experience training machine learning models from scratch, which includes architecture definition, dataset curation and cleaning, hyperparameter tuning, and moving models from research to monitored production
- Exposure to model optimization methodologies such as ONNX, TensorRT, quantization, and distillation
- Familiarity with infrastructure-as-code technologies including Terraform and CloudFormation
- Professional background in distributed systems or high-performance computing
- Previous contributions to open-source projects
Core Skills
Benefits
- Competitive compensation package
- Well-deserved time off
- Benefits designed to support health for employees and their families
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this position remote?
Yes, the posting notes that Clariti operates as a remote company, though occasional travel 1 to 2 times per year is expected for departmental or company-wide in-person meetings.
What is the salary range for the Senior MLOps Engineer role?
The base salary range is expected to be between $150,000 and $200,000 CAD, determined by qualifications, experience, skills, and internal pay equity.
What type of background check is required?
Successful candidates must undergo comprehensive background checks focusing strictly on global sanctions and relevant criminal offenses.
How can applicants request hiring accommodations?
Applicants requiring accommodations during the application, interview, or testing process can reach out directly via email to hr@claritisoftware.com.
Sample Interview Questions
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