Clariti
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Senior MLOps Engineer
role at
Clariti . We empower governments to deliver exceptional citizen experiences. How you will help us make an impact?
The
Senior MLOps Engineer
will design, build, and scale the systems that power CivCheck and Clariti's AI capabilities. As the first MLOps Engineer, you will lead the development of robust ML infrastructure, ensuring that models move efficiently from research to production with reliability, observability, and performance at scale. This role is ideal for someone who thrives at the intersection of machine learning, software engineering, and cloud infrastructure, and who is motivated to enable teams to deliver high‑impact ML systems efficiently and safely. Key Responsibilities
Design and maintain end‑to‑end ML pipelines for training, evaluation, and deployment of models and agentic AI workflows. Build and optimize infrastructure for distributed training and model serving across GPU and cloud environments. Develop tools for data creation, model versioning, experiment & performance tracking, and automated retraining. Collaborate with AI researchers and ML engineers to productionize POCs and ensure model reproducibility and scalability. Implement CI/CD best practices for ML systems, including continuous integration, automated testing, and deployment workflows. Monitor and manage model health, performance, drift, and data quality in production. Partner with Engineering teams to streamline infrastructure provisioning and data access. Drive cost optimization and performance tuning for large‑scale model training. Contribute to internal documentation and best practices. What you bring to the team
6–10+ years of experience in software or ML engineering, with at least 3+ in MLOps or ML infrastructure. Solid experience working with Python, C, C++, Bash, etc. Proven experience deploying and managing ML models in production. Proficiency with Docker and Kubernetes for scalable ML system design. Experience with cloud platforms (AWS, GCP, or Azure) and GPU orchestration. Hands‑on knowledge of CI/CD pipelines (GitHub Actions, Jenkins, or similar). Familiarity with MLflow, Weights & Biases, Kubeflow, and other similar tools for experiment tracking and pipeline automation. Solid understanding of data versioning, model reproducibility, and monitoring strategies. Excellent problem‑solving skills and a collaborative, team‑oriented mindset. Bonus Points
Experience training models from scratch, including defining architectures, curating & cleaning datasets, tuning training parameters, and bringing models from research to monitored production. Exposure to model optimization techniques (quantization, distillation, TensorRT, ONNX). Familiarity with infrastructure‑as‑code tools (Terraform, CloudFormation). Background in distributed systems or high‑performance computing. Contributions to open‑source projects. Benefits & Compensation
The base salary range for this role is expected to be between
$190,000-240,000
based on the candidate's skills, experience, and qualifications while considering internal pay equity and our broader pay philosophy. Benefits depend on employment type (full‑time, part‑time, contract, etc). Other Information
Background checks: Because our customers trust us with sensitive information, we require all successful candidates to undergo comprehensive background checks before joining our team. Travel: Although we operate as a remote company, all roles are expected to participate in occasional travel for in‑person company‑wide or departmental meetings, typically 1‑2 times per year. We are committed to building an inclusive culture where our team members take ownership over projects, tasks, and outcomes; bring a growth mindset to drive continuous learning and self‑development; and are customer‑focused by keeping the customer at the heart of decision‑making. We welcome and encourage candidates of all backgrounds to apply. If you require accommodations in completing an application, interviewing, completing any pre‑employment testing, or otherwise participating in our hiring process, please direct your questions to
hr@claritisoftware.com .
#J-18808-Ljbffr
Senior MLOps Engineer
role at
Clariti . We empower governments to deliver exceptional citizen experiences. How you will help us make an impact?
The
Senior MLOps Engineer
will design, build, and scale the systems that power CivCheck and Clariti's AI capabilities. As the first MLOps Engineer, you will lead the development of robust ML infrastructure, ensuring that models move efficiently from research to production with reliability, observability, and performance at scale. This role is ideal for someone who thrives at the intersection of machine learning, software engineering, and cloud infrastructure, and who is motivated to enable teams to deliver high‑impact ML systems efficiently and safely. Key Responsibilities
Design and maintain end‑to‑end ML pipelines for training, evaluation, and deployment of models and agentic AI workflows. Build and optimize infrastructure for distributed training and model serving across GPU and cloud environments. Develop tools for data creation, model versioning, experiment & performance tracking, and automated retraining. Collaborate with AI researchers and ML engineers to productionize POCs and ensure model reproducibility and scalability. Implement CI/CD best practices for ML systems, including continuous integration, automated testing, and deployment workflows. Monitor and manage model health, performance, drift, and data quality in production. Partner with Engineering teams to streamline infrastructure provisioning and data access. Drive cost optimization and performance tuning for large‑scale model training. Contribute to internal documentation and best practices. What you bring to the team
6–10+ years of experience in software or ML engineering, with at least 3+ in MLOps or ML infrastructure. Solid experience working with Python, C, C++, Bash, etc. Proven experience deploying and managing ML models in production. Proficiency with Docker and Kubernetes for scalable ML system design. Experience with cloud platforms (AWS, GCP, or Azure) and GPU orchestration. Hands‑on knowledge of CI/CD pipelines (GitHub Actions, Jenkins, or similar). Familiarity with MLflow, Weights & Biases, Kubeflow, and other similar tools for experiment tracking and pipeline automation. Solid understanding of data versioning, model reproducibility, and monitoring strategies. Excellent problem‑solving skills and a collaborative, team‑oriented mindset. Bonus Points
Experience training models from scratch, including defining architectures, curating & cleaning datasets, tuning training parameters, and bringing models from research to monitored production. Exposure to model optimization techniques (quantization, distillation, TensorRT, ONNX). Familiarity with infrastructure‑as‑code tools (Terraform, CloudFormation). Background in distributed systems or high‑performance computing. Contributions to open‑source projects. Benefits & Compensation
The base salary range for this role is expected to be between
$190,000-240,000
based on the candidate's skills, experience, and qualifications while considering internal pay equity and our broader pay philosophy. Benefits depend on employment type (full‑time, part‑time, contract, etc). Other Information
Background checks: Because our customers trust us with sensitive information, we require all successful candidates to undergo comprehensive background checks before joining our team. Travel: Although we operate as a remote company, all roles are expected to participate in occasional travel for in‑person company‑wide or departmental meetings, typically 1‑2 times per year. We are committed to building an inclusive culture where our team members take ownership over projects, tasks, and outcomes; bring a growth mindset to drive continuous learning and self‑development; and are customer‑focused by keeping the customer at the heart of decision‑making. We welcome and encourage candidates of all backgrounds to apply. If you require accommodations in completing an application, interviewing, completing any pre‑employment testing, or otherwise participating in our hiring process, please direct your questions to
hr@claritisoftware.com .
#J-18808-Ljbffr