Aspire | Full time
MLOps Engineer
Remote Job | Posted on 02/02/2025
Design, build, and maintain scalable ML pipelines for training, testing, and deploying models.
Implement CI/CD workflows for ML models and integrate them with existing infrastructure.
Develop and maintain monitoring, logging, and alerting systems for ML models in production.
Ensure reproducibility, versioning, and governance of ML models and datasets.
Optimize model serving infrastructure to improve latency, scalability, and cost-efficiency.
Automate feature engineering, model retraining, and performance evaluation workflows.
Ensure security, compliance, and best practices in handling ML artifacts and sensitive data.
Work with Kubernetes, Docker, and cloud services (AWS, GCP, or Azure) for scalable model deployment.
3+ years of experience in a similar role.
Bachelor’s degree in software engineering or any IT-related field.
Strong proficiency in Python and ML frameworks like TensorFlow, PyTorch, or Scikit-Learn.
Experience with ML model deployment using Kubernetes, Docker, or serverless architectures.
Hands-on experience with CI/CD tools such as GitHub Actions, Jenkins, or ArgoCD.
Familiarity with data versioning and model tracking tools like MLflow, DVC, or Kubeflow.
Experience in cloud-based ML solutions (AWS SageMaker, GCP Vertex AI, or Azure ML).
Knowledge of observability tools such as Prometheus, Grafana, and ELK stack.
Understanding of infrastructure as code (Terraform, CloudFormation) and configuration management (Ansible, Helm).
Excellent problem-solving and communication skills.
Awareness or knowledge of IT security best practices as defined by ISO / SOC or similar
Why Aspire
In addition to a competitive long-term total compensation with salary and performance-based bonus, we have a reward philosophy that expands beyond this.
