MLOps Engineer

Arkhya Tech. Inc.; Scottsdale (AZ); On-site; USD 140,000 - 180,000; Full time

Job summary

Arkhya Tech. Inc. in Scottsdale, AZ is seeking an experienced ML Engineer to design and implement end-to-end ML pipelines from data ingestion to model deployment.

The role includes building CI/CD pipelines for ML models, automating monitoring and retraining, and collaborating with data scientists and engineers to productionize models. You will ensure scalability, reliability, and security of ML systems while managing model versioning, experiment tracking, and governance.

Qualifications

• Strong Python programming skills.
• Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with MLOps tools: MLflow, Kubeflow, Airflow, SageMaker, Azure ML.

Responsibilities

• Design and implement end-to-end ML pipelines from data ingestion to deployment.
• Build and manage CI/CD pipelines for ML models (training, testing, deployment).
• Automate model monitoring, retraining, and performance optimization.
• Collaborate with Data Scientists and Data Engineers for productionizing ML models.
• Ensure scalability, reliability, and security of ML systems.
• Manage model versioning, experiment tracking, and lifecycle management.
• Implement governance, compliance, and reproducibility best practices.

Skills

Python

ML frameworks

MLOps tools

CI/CD tools

AWS

Data pipelines/ETL

Tools

MLflow

Kubeflow

Airflow

SageMaker

Azure ML

Jenkins

GitHub Actions

GitLab CI

Job description

• Design and implement end-to-end ML pipelines from data ingestion to model deployment
• Build and manage CI/CD pipelines for ML models (training, testing, deployment)
• Automate model monitoring, retraining, and performance optimization
• Collaborate with Data Scientists and Data Engineers for productionizing ML models
• Ensure scalability, reliability, and security of ML systems
• Manage model versioning, experiment tracking, and lifecycle management
• Implement best practices for governance, compliance, and reproducibility

Key Skills & Expertise

• Strong programming skills in Python
• Experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn
• Hands-on experience with MLOps tools: MLflow, Kubeflow, Airflow, SageMaker, Azure ML
• Knowledge of CI/CD tools: Jenkins, GitHub Actions, GitLab CI
• Experience with cloud platforms: AWS
• Strong understanding of data pipelines, ETL processes, and distributed systems