MLOps Engineer
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MidFull-time
#402951·Dodano wczoraj·0
Źródło: nofluffjobs.comTech Stack / Keywords
KubernetesTerraformMLOpsKubeflowAirflowAWS
Wymagania
- Bachelor’s degree in Computer Science, Engineering, or related field
- 2+ years of hands-on experience in MLOps, DevOps, or related fields
- Knowledge and preferable experience with AWS services for machine learning incl. SageMaker, EKS, S3, EC2, Lambda
- Exposure to Kubernetes for container orchestration
- Experience with Docker
- Experience with infrastructure-as-code tools like Terraform or CloudFormation
- Familiarity with CI/CD tools such as GitLab CI
- Understanding of machine learning model lifecycle
- Familiarity with monitoring and logging solutions like Prometheus, Grafana, CloudWatch, and ELK Stack
- Understanding of networking concepts and cloud security best practices
- Proficiency in Python and Bash; comfortable with Linux environments
Nice to have:
- Experience with serverless architectures and event-driven processing on AWS
- Familiarity with advanced Kubernetes concepts such as Helm
- Experience with Data Engineering pipelines, ETL, or big data platforms
- Experience with ML frameworks like TensorFlow, PyTorch, and Keras
- Experience with ML platforms like Kubeflow and/or SageMaker
- Experience with workflow engines like Argo Workflows and/or Airflow
Obowiązki
- Assist in designing, implementing, and maintaining scalable MLOps pipelines on AWS using services such as SageMaker, EC2, EKS, S3, and Lambda
- Coordinate with platform team to troubleshoot Kubernetes clusters (EKS) for deploying machine learning models and microservices
- Develop and maintain CI/CD pipelines for model and application deployment, testing, and monitoring
- Collaborate with Data Science and DevOps teams to streamline model development lifecycle from experimentation to production
- Implement security best practices in AWS infrastructure including network security, data encryption, and role-based access controls
- Monitor, troubleshoot, and optimize data and ML pipelines for high availability and performance
- Set up and manage model monitoring systems for performance drift ensuring continuous improvement
Benefity
- Attractive remuneration package plus performance-related reward
- Intellectually stimulating work environment
- Continuous personal development and international training opportunities
Inne informacje
All applications will be treated with strict confidentiality!
XM
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