AI Engineer / Machine Learning Engineer – MLOps
New
K
KATBOTZ LLCMachine Learning
United StatesFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 3–7 years in Machine Learning / AI / Data Engineering; 2+ years in MLOps / Model Deployment / ML Pipelines
- Required Skills
- AWSDockerPythonGCPKubeflowKubernetesMachine LearningMLFlowAirflowAzureCI/CD
Requirements
- 3–7 years of experience in Machine Learning / AI / Data Engineering
- 2+ years of experience in MLOps, Model Deployment, or ML Pipelines
- Proficiency in Python and machine learning concepts
- Experience with Docker and Kubernetes for containerization
- Experience deploying machine learning models into production
- Experience with CI/CD tools such as GitHub Actions, Jenkins, or GitLab CI
- Experience with cloud platforms like AWS, Azure, or GCP
- Familiarity with MLOps tools such as MLflow, Kubeflow, Airflow, or DVC
- Familiarity with SQL and NoSQL databases
- Experience with model monitoring, logging, and performance tracking
- Ability to work with FastAPI or Flask for API development
Responsibilities
- Build and maintain ML pipelines for training, testing, and deployment
- Deploy machine learning and AI models into production environments
- Manage model lifecycle (training, deployment, monitoring, retraining)
- Automate workflows using CI/CD for ML models
- Monitor model performance, drift, and data quality
- Work with data scientists and AI developers to productionize models
- Manage model versioning, data versioning, and experiment tracking
- Deploy models on cloud platforms (AWS, Azure, GCP)
- Containerize applications using Docker and Kubernetes
- Implement monitoring and logging for ML systems
- Ensure scalability, security, and reliability of AI systems
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