Senior Software Engineer, MLOps Platform - Autonomous Vehicles

This job was posted over 30 days ago, so it has most likely closed. See newer jobs like it.

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.

Job Overview

The Senior Software Engineer for the MLOps Platform focused on Autonomous Vehicles at NVIDIA will be tasked with developing and optimizing scalable machine learning solutions that enhance the performance and reliability of autonomous systems. This role entails architecting and implementing MLOps pipelines, collaborating with cross-functional teams to ensure seamless integration of machine learning models into production environments, and driving innovations that improve the efficiency of model training and deployment processes.

Job Responsibilities

• Design, develop, and maintain robust MLOps frameworks for autonomous vehicle applications.
• Collaborate closely with data scientists to streamline the deployment of machine learning models into production.
• Implement CI/CD pipelines to accelerate model updates and ensure high availability.
• Conduct performance tuning and optimization of deployed models for real-time inference.
• Monitor and troubleshoot production systems to ensure optimal performance of the MLOps platform.
• Advocate for and implement best practices in model versioning, data management, and experiment tracking.
• Lead initiatives for continuous improvement in tooling, processes, and workflows within the MLOps team.

Qualifications

• Bachelor’s or advanced degree in Computer Science, Engineering, or a related technical field.
• 5+ years of software engineering experience, with a focus on MLOps or machine learning infrastructure.
• Proficient in programming languages such as Python, C++, or Java.
• Strong understanding of cloud computing platforms (e.g., AWS, GCP, Azure) and container orchestration (Docker, Kubernetes).
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.
• Demonstrated experience with DevOps practices and tools relevant to CI/CD pipelines.
• Excellent problem-solving skills and ability to work in a fast-paced, team-oriented environment.

Technologies & Tools

The Senior Software Engineer will leverage a variety of technologies and tools including cloud computing platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure. Additionally, proficiency in containerization technologies like Docker and orchestration tools such as Kubernetes will be essential for managing scalable applications. Familiarity with machine learning libraries and tools, alongside version control systems like Git, is crucial for streamlining the software development lifecycle within the MLOps framework.

Ideal Candidates

Ideal candidates for this position at NVIDIA will possess a blend of technical proficiency and innovative thinking. They will demonstrate a strong passion for advancing autonomous technology, showcasing adaptability in evolving project requirements. A collaborative mindset and effective communication skills are essential for working closely with diverse teams, coupled with a proactive approach to problem-solving that drives impactful results. Furthermore, a focus on continuous learning and keeping up with industry advancements will amplify their contributions to the team and drive success in the rapidly transforming field of autonomous vehicles.