Senior MLOps Automation Engineer - AV Infrastructure

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

Overview

The Senior MLOps Automation Engineer - AV Infrastructure at NVIDIA is responsible for bridging machine learning and operational excellence within the audiovisual infrastructure domain. The ideal candidate will design, implement, and maintain automated systems that enhance machine learning model deployment, monitoring, and maintenance, ensuring seamless integration with existing infrastructure. By leveraging strong expertise in MLOps methodologies and best practices, the successful applicant will contribute significantly to improving the reliability, scalability, and performance of NVIDIA's audiovisual technologies.

Job Responsibilities

• Design, develop, and implement automated MLOps processes for model deployment and monitoring.
• Work closely with data scientists and software engineers to streamline collaborations across teams.
• Establish and optimize continuous integration/continuous deployment (CI/CD) pipelines for machine learning workflows.
• Monitor and maintain the health and performance of deployed models in production environments.
• Develop infrastructure solutions to enhance capacity planning, resource allocation, and performance tuning.
• Implement best practices for version control, model cataloging, and experimentation tracking.
• Collaborate with cross-functional teams to integrate machine learning models into existing AV systems.
• Document processes, standards, and best practices to foster knowledge sharing and operational efficiency.

Qualifications

• A bachelor's degree in Computer Science, Engineering, or related field; a master's degree is preferred.
• 5+ years of experience in MLOps, DevOps, or a similar role with a focus on automation.
• Proven experience with CI/CD tools and practices, such as Jenkins, GitLab, or similar.
• Strong programming skills in Python, along with experience in Cloud infrastructure platforms (AWS, Azure, GCP).
• Familiarity with machine learning frameworks (TensorFlow, PyTorch, etc.) and their operational aspects.
• Proficiency in containerization technology (Docker, Kubernetes) and orchestration tools.
• Excellent problem-solving skills and the ability to work in a fast-paced environment.
• Strong communication skills, with the ability to collaborate across various teams and stakeholders.

Technologies & Tools

The Senior MLOps Automation Engineer will be utilizing an array of technologies and tools, including but not limited to Docker for containerization, Kubernetes for orchestration, cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure, CI/CD tools like Jenkins or GitLab, and machine learning frameworks including TensorFlow or PyTorch. Proficiency in scripting languages such as Python will also be essential for automation tasks.

Ideal Candidates

The ideal candidates for the Senior MLOps Automation Engineer position possess a strong passion for innovation and the ability to adapt to evolving technologies. They should showcase a proactive attitude towards problem-solving and display a complete grasp of the complexities related to machine learning and operational workflows. Furthermore, these individuals must exhibit excellent collaboration abilities, celebrate teamwork, and continuously seek improvement. A keen eye for detail, methodological approaches to challenges, and a commitment to best practices are critical to ensuring success in this role.