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The company is looking to solve the problem of democratizing access to AI infrastructure and empowering organizations to create, optimize, and deploy AI solutions at any scale by simplifying the complexities of AI development with a full-stack AI platform.

Requirements

• 5+ years of experience with cloud technologies and infrastructure, ideally in senior MLOps or Solutions Architect roles
• Proven expertise in scaling and optimizing AI workloads across multi-node and multi-GPU environments
• Demonstrated success delivering ML products, scaling from POC to production
• Deep knowledge of ML frameworks like PyTorch and JAX
• Strong background in the NVIDIA HPC ecosystem (CUDA, NCCL, Infiniband)
• Programming Languages: Python, Go, Java, C++
• Infrastructure as Code (IaC): Terraform, Ansible

Responsibilities

• Architect and optimize distributed training and inference systems for large-scale AI models
• Design and deliver customer-focused solutions that maximize performance and business value
• Lead the transition of ML pipelines from POC to scalable production systems
• Create whitepapers, deliver technical presentations, and host webinars to share insights and best practices
• Provide technical leadership and mentor teams on AI infrastructure and deployment strategies
• Collaborate with engineering and product teams to prioritize customer feedback and influence product roadmaps

Other

• Exceptional communication skills to engage both technical teams and business stakeholders
• Legal authorization to work in the United States on a full-time basis without sponsorship
• Remote U.S. candidate location