Remote Engineer DevOps (MLOps) | WFH

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Overview

The Remote Engineer DevOps (MLOps) position at Get It - Professional Services is a crucial role focused on integrating machine learning models into operational environments efficiently and reliably. The successful candidate will be responsible for designing, implementing, and maintaining scalable and robust MLOps pipelines. This role requires active collaboration with cross-functional teams to ensure seamless connectivity between data engineering, machine learning, and IT operations while promoting best practices in version control, CI/CD processes, and monitoring for improved performance and reliability.

Job Responsibilities

• Design and implement scalable MLOps solutions to support deployment and operation of machine learning models.
• Maintain and optimize infrastructure for data pipelines and production-level machine learning applications.
• Implement CI/CD pipelines for machine learning workflows, ensuring automation and efficiency.
• Monitor and troubleshoot performance and reliability of deployed models, making adjustments as needed to maintain performance.
• Collaborate with data scientists and engineers to ensure smooth transitions from model development to production.
• Develop and maintain documentation for MLOps processes and workflows, facilitating knowledge sharing across teams.
• Stay current with industry trends and best practices in MLOps and DevOps, incorporating improvements into workflows.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
• Minimum of 3 years of experience in a DevOps or MLOps role.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Familiarity with cloud services (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Strong understanding of CI/CD practices and experience with related tools (e.g., Jenkins, GitLab CI, CircleCI).
• Excellent problem-solving skills and ability to work collaboratively in a remote environment.

Technologies & Tools

The Remote Engineer DevOps (MLOps) will utilize a diverse range of technologies and tools including cloud platforms like AWS and Google Cloud Platform, container orchestration tools like Kubernetes and Docker, version control systems like Git, and CI/CD tools such as Jenkins and GitLab CI. Familiarity with big data technologies like Apache Spark or Hadoop, as well as monitoring solutions like Prometheus and Grafana, will also be beneficial in ensuring efficient operational workflows.

Ideal Candidates

The ideal candidate for the Remote Engineer DevOps (MLOps) position is someone who demonstrates exceptional analytical and problem-solving skills, thrives in a collaborative remote work environment, and possesses a strong desire to stay abreast of the latest developments in machine learning and DevOps practices. They should exemplify qualities such as adaptability, attention to detail, and excellent communication skills, enabling them to engage effectively with team members across various functions for successful project execution.