Remote DevOps Engineer (MLOps) | Work From Home

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Written by AI from the job title and company, not by Get It - Professional Services, so some details may not match this job. The employer's own page has the real description.

Overview

As a Remote DevOps Engineer specializing in MLOps at Get It - Professional Services, you will play a pivotal role in enhancing our machine learning operational workflows. Your primary responsibility will encompass the design, implementation, and maintenance of robust MLOps pipelines to streamline the deployment, monitoring, and governance of machine learning models. This position requires a proactive approach to collaboration with data scientists and software engineers to establish seamless integration between both environments, ensuring high availability and performance of our ML applications in a cloud-based setting.

Job Responsibilities

• Design and implement MLOps pipelines to support the deployment, monitoring, and scalability of machine learning models.
• Collaborate with data scientists to understand model requirements and ensure smooth transition from development to production.
• Utilize cloud services for optimal resource management and model serving.
• Monitor and troubleshoot production ML systems to ensure high availability and performance.
• Automate repetitive tasks through scripting and efficient workflows.
• Implement and manage CI/CD processes for ML models and associated infrastructure.
• Adhere to compliance and security standards throughout the MLOps lifecycle.
• Contribute to knowledge sharing and documentation of best practices in MLOps.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, or a related field.
• Proven experience as a DevOps Engineer or MLOps Engineer.
• Strong knowledge of cloud platforms (AWS, Azure, GCP) and container orchestration tools (Docker, Kubernetes).
• Experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) and data engineering tools.
• Proficiency in scripting languages such as Python, Bash, or similar.
• Understanding of CI/CD principles and tools (Jenkins, GitLab, CircleCI).
• Familiarity with infrastructure as code tools (Terraform, Ansible).
• Strong problem-solving skills and the ability to work independently.

Technologies & Tools

In this role, you will leverage a variety of technologies and tools to facilitate efficient MLOps practices. Key platforms include AWS, Azure, or Google Cloud for cloud computing; Docker and Kubernetes for containerization and orchestration; along with CI/CD tools like Jenkins and GitLab for continuous integration and deployment. Moreover, familiarity with machine learning frameworks such as TensorFlow and PyTorch will be essential for coordinating with data science teams effectively.

Ideal Candidates

The ideal candidate for the Remote DevOps Engineer (MLOps) position will possess a blend of technical expertise and interpersonal skills. They should demonstrate a strong passion for machine learning and automation, coupled with an aptitude for problem-solving in fast-paced environments. Excellent communication skills are essential, as collaboration with cross-functional teams will be a core aspect of the role. A proactive attitude, adaptability to new technologies, and a commitment to best practices in MLOps will be key characteristics of a successful candidate.