Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience
3+ years of technical program management experience in infrastructure, cloud platforms, or ML/AI systems
Strong technical background with ability to engage in architecture discussions around distributed systems, GPU computing, or ML frameworks
Proven track record of delivering complex, multi-quarter programs involving hardware and software components
Experience managing cross-functional initiatives with engineering, product, and business stakeholders
Experience with Jira and implementing Jira workflows to match team processes
Excellent written and verbal communication skills, with ability to tailor messaging for technical and non-technical audiences
Experience with AMD GPU architectures (ROCm, Instinct GPUs) or competitive platforms (NVIDIA CUDA, Google TPUs)
Background in ML infrastructure, model training/inference pipelines, or MLOps platforms
Prior experience at a high-growth startup or in a fast-paced infrastructure organization
Hands-on technical experience as a software engineer or systems engineer earlier in career
Familiarity with Kubernetes, distributed training frameworks (PyTorch, JAX), or AI workload orchestration