Senior Machine Learning Infrastructure Engineer

About the role

PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.

As a Senior ML Infrastructure Engineer at Plus, you will design scalable architectures capable of handling petabytes of data while ensuring optimal performance for both training and inference phases. You will build robust pipelines for managing model versioning systems and experiment tracking frameworks, which are essential for maintaining reproducibility across experiments. Additionally, you will be responsible for managing large-scale GPU clusters. This role offers unparalleled opportunities—both technically and professionally—for individuals passionate about solving challenging problems using modern cloud-native technologies. Ideal candidates thrive in environments that leverage tools such as Docker containers orchestrated via Kubernetes clusters, seamlessly integrated with state-of-the-art deep learning frameworks like PyTorch or TensorFlow. If you are eager to push the boundaries of what's possible in machine learning infrastructure and contribute to cutting-edge solutions, this position is an excellent fit!

Responsibilities: - Design and develop scalable, high-performance systems for training, inference, deploying, and monitoring ML models at scale.

- Build and maintain efficient data pipelines, model versioning systems, and experiment tracking frameworks.

- Collaborate with cross-functional teams, including ML researchers and engineers, to identify bottlenecks and improve platform usability.

- Implement distributed systems and storage solutions optimized for machine learning workloadsDrive improvements in CI/CD workflows for ML models and infrastructure.

- Ensure high availability and reliability of the ML platform by implementing robust monitoring, logging, and alerting systems.

- Stay current with industry trends and integrate relevant tools and frameworks to enhance the platform.

- Mentor junior engineers and contribute to a culture of technical excellence

- Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts.

- Ensure team compliance with QMS, monitor quality, and drive process improvements.

Required Skills: - Phd or MS in Computer Science, Electrical Engineering, or related field

- Good oral and written communication skills

- Phd new grad or Masters with 3+ years of software engineering experience with a focus on ML infrastructure or distributed systems.