Design and implement scalable AI solutions for a leading AI cloud platform. Architect distributed training and inference systems for large-scale models, and lead ML pipeline transitions from POC to production.
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
Build long-term customer relationships and provide technical leadership
Create whitepapers, deliver technical presentations, and host webinars
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
Deep knowledge of ML frameworks like PyTorch and JAX
Strong background in NVIDIA HPC ecosystem (CUDA, NCCL, Infiniband)
Hirevector is a professional services and recruitment firm that provides an AI-powered technical interview intelligence platform. The company focuses on standardizing the hiring process through conversational, AI-driven assessments to ensure fairness, reduce bias, and improve candidate evaluation.