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

As a Senior MLOps Automation Engineer for AV Infrastructure at NVIDIA, you will play a critical role in enhancing the performance and automation of machine learning operations within our audio and visual (AV) infrastructure. You will be responsible for developing robust deployment pipelines, ensuring reliability and scalability of AV frameworks, and optimizing workflows that facilitate machine learning model deployment. Your expertise will drive the enhancement of existing systems while paving the way for innovative approaches to automation and integration across diverse AV projects.

Job Responsibilities

• Design and implement scalable MLOps workflows for audio and visual data processing.
• Automate deployment, monitoring, and performance optimization of machine learning models in production.
• Collaborate with cross-functional teams to integrate machine learning solutions into existing systems.
• Maintain and enhance CI/CD pipelines tailored for MLOps within the AV infrastructure.
• Develop strategies for the efficient management of data pipelines and model versioning.
• Identify opportunities to streamline processes, reduce latency, and increase the reliability of AV applications.
• Conduct thorough testing and validation of models, ensuring quality and accuracy prior to deployment.
• Provide technical guidance and mentoring to junior engineers and interns.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field; Master’s degree preferred.
• 5+ years of experience in MLOps, machine learning, or software engineering.
• Proficiency in programming languages such as Python, Java, or C++.
• Strong experience with CI/CD tools and frameworks, including Jenkins, Git, and Docker.
• Familiarity with machine learning frameworks like TensorFlow, PyTorch, or similar.
• Knowledge of cloud platforms such as AWS, Google Cloud, or Azure for deploying and managing ML applications.
• Excellent problem-solving skills and a strong analytical mindset.
• Strong communication and collaboration skills to work effectively in a team-oriented environment.

Technologies & Tools

This position leverages a variety of leading-edge technologies and tools for machine learning and automation, including cloud platforms (AWS, Google Cloud, Azure), MLOps frameworks (Kubeflow, MLflow), containers (Docker, Kubernetes), and CI/CD tools (Jenkins, Gitlab CI). Familiarity with AV processing libraries and APIs will be crucial, as well as proficiency in scripting languages and tools that enhance data pipeline efficiency.

Ideal Candidates

Ideal candidates for this role are detail-oriented professionals with a strong background in MLOps and software engineering. They possess a keen understanding of both machine learning principles and AV technology, allowing them to bridge the gap between data science and engineering. Self-motivated individuals who thrive in collaborative environments and are eager to innovate will find this position particularly rewarding. Strong communicators, who can articulate complex technical concepts to non-technical stakeholders, will excel in this role.