A place where work is not just work, it is Responsibility.
Arfa Solutions • Talent Pool • Recruitment • Placement Support • Placement
11 - 50 employees
February 11
🇺🇸 United States – Remote
⏳ Contract/Temporary
🟡 Mid-level
🟠 Senior
⛑ DevOps & Site Reliability Engineer (SRE)
Airflow
Apache
AWS
Azure
Cloud
Docker
Google Cloud Platform
Java
Jenkins
Kubernetes
Python
PyTorch
Scikit-Learn
Tensorflow
A place where work is not just work, it is Responsibility.
Arfa Solutions • Talent Pool • Recruitment • Placement Support • Placement
11 - 50 employees
•ARFA Solutions, LLC is looking for a skilled DevOps (MLOps) Engineer to help streamline and enhance our machine learning operations. •As an MLOps Engineer, you will be responsible for deploying machine learning models into production, automating the workflow, and implementing best practices for continuous integration and continuous delivery (CI/CD) in MLOps. •You will work closely with data scientists, developers, and IT operations teams to ensure smooth and efficient operations. •Responsibilities: •Design, implement, and manage MLOps pipelines for deploying and monitoring machine learning models. •Collaborate with data scientists to understand model requirements and operationalize models into production environments. •Automate model training, testing, and deployment processes through CI/CD principles. •Monitor and evaluate model performance in production and implement solutions for improvement. •Implement data versioning, model versioning, and tracking systems to ensure reproducibility. •Ensure security and compliance in the deployment of machine learning models. •Document processes and improve collaboration between teams for efficient workflows. •Stay up-to-date with industry trends and technologies in MLOps and machine learning.
•Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field. •5+ years of experience in DevOps or MLOps roles. •Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. •Proficiency in programming languages such as Python, R, or Java. •Strong understanding of cloud platforms (AWS, Azure, or GCP) and their machine learning services. •Experience with containerization technologies, particularly Docker, and orchestration tools like Kubernetes. •Knowledge of CI/CD tools like Jenkins, GitLab CI/CD, or Azure DevOps. •Familiarity with data pipeline tools and frameworks, such as Apache Airflow or Kubeflow. •Strong problem-solving and analytical skills. •Excellent communication and teamwork abilities.
•A Remote work environment. •1099 or C2C
Apply NowDecember 9, 2024
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