AI Engineer – New College Graduate

This is a fully remote position, open to applicants in California, +1 more state.

📋 Description

• Design and implement large-scale, highly available AI cloud services, such as GPU virtual machines, bare-metal offerings, container solutions, cloud networking, storage, billing, monitoring, security, and multi-region resource management.

• Create managed Kubernetes services featuring GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for extensive AI training and inference operations.

• Develop capabilities for distributed training, model fine-tuning, model deployment, inference acceleration, serverless inference, model APIs, model evaluation, and production-grade LLM and multimodal model-serving.

• Build enterprise AI Agent platforms that encompass Agent creation, workflow orchestration, tool integration, retrieval-augmented generation, memory systems, sandbox execution, multi-Agent collaboration, evaluation, observability, security, and large-scale Agent runtime infrastructure.

• Work on GPU resource scheduling, distributed systems, high-performance networking, cloud-native infrastructure, MLOps and LLMOps platforms, AI application marketplaces, and automated operational systems for large-scale AI infrastructures.

• Begin in one of the specified technical areas based on interview evaluation and organizational requirements.

• Participate in rotations across various roles as part of your career progression.

⛳️ Requirements

• Recent graduates (Bachelors, Masters, PhD) from all fields and/or individuals with up to 2 years of relevant work experience.

• Proficient programming skills in one or more languages, such as Go, Python, C++, Java, Rust, or related technologies.

• Preferred experience with Kubernetes, Docker, Helm, Terraform, OpenStack, Prometheus, Grafana, Argo, Istio, PostgreSQL, Redis, message queues, distributed storage, or other cloud-native technologies.

• Highly preferred experience in developing or managing large-scale cloud platforms, Kubernetes environments, AI training platforms, inference platforms, or Agent platforms.

• Strong passion for cutting-edge AI infrastructure, cloud-native technologies, and the construction of large-scale, globally distributed systems.

• Demonstrated accomplishments in academics, engineering projects, prestigious publications, open-source contributions, or programming/algorithm competitions.

• A robust ownership mentality and engineering discipline.

• Dedication to making a meaningful impact early in your career.

🏝️ Benefits

• Opportunities to explore various roles as part of career development.

• A culture that appreciates authenticity and diverse viewpoints.

• An inclusive and respectful environment featuring open workspaces and a dynamic start-up atmosphere.

• Chances to connect with industry leaders and enthusiasts.

• The ability to make a direct contribution and influence the future of the digital asset and AI computing sectors.

• Engagement in new projects and the development of processes and systems.

• Personal accountability, autonomy, rapid growth, and opportunities for learning.

• Access to training and mentorship.

• Equal employment opportunities.