Senior MLOps Automation Engineer - AV Infrastructure

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Job Overview

As a Senior MLOps Automation Engineer specializing in AV Infrastructure at NVIDIA, you will be responsible for designing, implementing, and managing automated systems that enhance our machine learning operations. This role involves close collaboration with cross-functional teams to ensure seamless integration of Machine Learning (ML) models into production environments while optimizing operational efficiency and performance. You will spearhead initiatives to streamline workflows, improve automation, and utilize best practices in ML deployment and monitoring. Your expertise will drive advancements in our AV product offerings, following industry standards and NVIDIA's innovative ethos.

Job Responsibilities

• Design and implement automated pipelines for ML model training, validation, and deployment.
• Collaborate with software engineers, data scientists, and product managers to define and optimize ML workflows.
• Maintain and enhance existing MLOps tools and frameworks to ensure high availability and reliability.
• Monitor and troubleshoot production ML systems, analyzing performance metrics and incorporating feedback for continuous improvement.
• Contribute to developing best practices for operationalizing machine learning initiatives at scale.
• Provide technical guidance and mentorship to junior engineers, promoting knowledge sharing across teams.
• Lead efforts to document processes, tools, and standards related to MLOps automation.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in MLOps, Data Engineering, or a similar role.
• Strong proficiency in programming languages such as Python, Java, or Go.
• Solid understanding of machine learning frameworks such as TensorFlow, PyTorch, or similar.
• Experience with orchestration and automation tools like Kubernetes, Docker, Airflow, or similar.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their respective ML services.
• Excellent problem-solving skills and ability to work in a fast-paced environment.

Technologies & Tools

The Senior MLOps Automation Engineer will utilize a variety of technologies and tools, including but not limited to Docker for containerization, Kubernetes for orchestration, Apache Airflow for workflow management, as well as machine learning libraries such as TensorFlow and PyTorch. Exposure to cloud platforms, including AWS, Google Cloud, or Microsoft Azure, will also be essential in facilitating seamless deployment and scaling of machine learning applications.

Ideal Candidates

The ideal candidate for this position will possess a deep passion for machine learning and operational excellence, coupled with a proactive mindset that fosters innovation. You should have an analytical approach to problem-solving and a strong ability to work collaboratively within diverse teams. Leadership qualities, combined with excellent communication skills, will be vital as you mentor junior engineers and interface with multiple stakeholders. A strong commitment to quality, efficiency, and a continuous improvement mindset will also be integral to your success in this role at NVIDIA.