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Location: Remote (Romania)
Type: Full-Time
We are looking for a skilled AI/MLOps Engineer to own the deployment, monitoring, and continuous delivery of machine learning models in production environments. You will bridge the gap between data science and engineering — ensuring models are reliable, scalable, and performing as expected at all times. This is a fully remote role ideal for someone who is equally comfortable with ML pipelines and cloud infrastructure.
Responsibilities
Requirements
Type: Full-Time
We are looking for a skilled AI/MLOps Engineer to own the deployment, monitoring, and continuous delivery of machine learning models in production environments. You will bridge the gap between data science and engineering — ensuring models are reliable, scalable, and performing as expected at all times. This is a fully remote role ideal for someone who is equally comfortable with ML pipelines and cloud infrastructure.
Responsibilities
- Deploy, manage, and monitor machine learning models in production environments
- Build and maintain CI/CD pipelines for ML workflows
- Automate model training, validation, versioning, and retraining pipelines
- Monitor model performance, detect drift, and trigger retraining when needed
- Manage cloud infrastructure for ML workloads on AWS, GCP, or Azure
- Collaborate with data scientists to package and productionize models
- Implement logging, alerting, and observability for ML systems
- Ensure security, scalability, and cost-efficiency of ML infrastructure
- Maintain documentation for all pipelines, deployments, and processes
- Evaluate and integrate MLOps tools and platforms (MLflow, Kubeflow,
Requirements
- 2–3 years of hands-on MLOps or ML engineering experience
- Strong Python skills — scripting, automation, and ML pipeline development
- Experience with CI/CD tools (GitHub Actions, Jenkins, GitLab CI, or similar)
- Hands-on experience with at least one major cloud platform: AWS, GCP, or Azure
- Familiarity with containerization and orchestration: Docker and Kubernetes
- Experience with model monitoring, versioning, and experiment tracking (MLflow, DVC, or similar)
- Solid understanding of ML concepts — model training, evaluation, and deployment
- Strong problem-solving skills and ability to work independently in a remote setting
- Experience with feature stores (Feast, Tecton, or similar)
- Knowledge of data pipeline tools (Apache Airflow, Prefect, or similar)
- Familiarity with LLM deployment and serving (vLLM, TGI, or similar)
- Experience with Terraform or infrastructure-as-code tools
- Exposure to real-time inference and model serving frameworks
Key Skills
Ranked by relevance
cloud
machine learning
mlflow
mlops
cicd
aws
gcp
continuous delivery
containerization
gitlab ci
terraform
jenkins
python
docker
apache
gitlab
ai
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- Posted
- Apr 10, 2026
- Type
- Full-time
- Level
- Not Applicable
- Location
- Romania
- Company
- DigiHyre
Industries
Human Resources Services
Categories
Information Technology
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3 roles aligned with this opportunity
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