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At ASI, we are revolutionizing industries with state-of-the-art autonomous robotics solutions. Within the fields of agriculture, construction, landscaping, and logistics, we deliver technologies that enhance safety, productivity, and efficiency. With our core values of Simplicity, Safety, Transparency, Humility, Attention to Detail and Growth guiding everything we do, we're shaping the future of automation in dynamic markets. As an AI Infrastructure Engineer IV, you will play a critical role in designing, building, and maintaining the systems that power our AI and machine learning capabilities. You will ensure our compute, storage, and cloud environments are scalable, efficient, and tuned for high-performance AI workloads. Working closely with data scientists, robotics engineers, and software teams, you'll develop robust infrastructure that supports the deployment and reliability of our AI-driven autonomous systems.
Job Responsibility:
Design, build, and maintain high-performance computing infrastructure including CPUs, GPUs, storage, and networking to support AI and ML workloads
Deploy and manage AI systems within cloud environments (AWS, Azure, GCP), ensuring scalability, cost-efficiency, and high availability
Collaborate with data scientists, ML engineers, and software teams to support AI model development, training, and deployment workflows
Implement automation, CI/CD, DevOps, and MLOps practices to create efficient, repeatable, and reliable AI infrastructure processes
Optimize compute and storage systems to achieve maximum performance and throughput for AI/ML pipelines
Monitor system health and troubleshoot performance bottlenecks, infrastructure issues, and deployment challenges
Requirements:
Bachelor's degree in Computer Science, Computer Engineering, or a related technical field
10+ years of experience in cloud infrastructure, DevOps, or platform engineering with an emphasis on AI/ML systems
Strong understanding of modern AI infrastructure components, including distributed computing, GPU-accelerated systems, and large-scale storage
Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud
Proficiency with Kubernetes, Docker, Terraform, or similar containerization and orchestration tools
Strong programming skills in Python and/or C++, with experience supporting machine learning frameworks (TensorFlow, PyTorch, etc.)
Experience implementing CI/CD pipelines, MLOps practices, and automation tooling
What we offer:
Full Benefits - 90% Medical, ESOP, 401K, Generous PTO