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Sr MLOPS/Devops Engineer
Salary undisclosed
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Education: Bachelor's degree in Computer Science or equivalent
Experience:
- Minimum8 years of related experience
- Required Systems Knowledge:
- Machine Learning:Proven experience with concepts and frameworks (TensorFlow, PyTorch, scikit-learn)
- ML Pipelines:Experience building and deploying pipelines using tools like Kubeflow, MLflow, or Airflow.
- Software Development:Strong understanding of best practices (version control, CI/CD).
On-Prem infrastructure build out of Containerization:Docker, Kubernetes (Rancher preferred) - Configuration Management:Yarn, Yaml files
- Infrastructure Management: Linux Patching, troubleshooting, Load Balancers, Certificate management
- On-Prem infrastructure build out of Version Control:GitLab/GitHub
- Big Data:Hadoop, Hive
- Data Visualization:Grafana, Prometheus, Elk
- Scripting:Python (specialist)
Preferred Systems Knowledge: - Big Data Storage Management:MapR storage, EMC Isilon, Vast storage
- Linux Administration:Advanced skills
- Scripting:Expertise in Python, bash, additional scripting languages Ruby
- Security:LDAP integration, Vault development
- Configuration Management:Ansible development
- Virtualization:VMware administration, Harvester
- Operating Systems:Experience with CentOS, RHEL, Ubuntu
- Data Science Tools:
- Kubernetes (Rancher), Helm, Operators, Ingress (nginx,traefik), Monitoring, Alerting, Observability, CI/CD
- Drill
Livy
- MapR
- Jupyter Notebooks
- Through understanding of implementing On-Prem R (Rstudio)
- On-Prem Infrastructure experience with Setting up GPUs for use with Pytorch, must be able to know how to test if the GPU is working on the system.
- Through understanding of NFS, S3, SMB, Cifs mounting.
- Through understanding with On-Prem Linux integration with Active Directory.
Preferred candidate to come from a health research background.
Note: Experience with these tools will be a strong advantage.
Additional Information:
The listed data science tools are commonly used in research settings and are relevant to the role.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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