Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience 5+ years of experience in one or more of the following areas: Software Engineering, Artificial Intelligence, Machine Learning, or a related field 3+ years of experience in Deep Learning, Model Fine-tuning, Inference Optimization, or Distributed Systems Direct experience working with modern foundational AI architectures (e.g., Transformers, Mixture-of-Experts, or hybrid/multimodal architectures) beyond API interactions (e.g., hands-on experience with weights, tokenizers, kernels, and model internals) Solid understanding of at least one Deep Learning framework (e.g., PyTorch or JAX) and the ability to read, translate, and contribute to large-scale inference codebases Experience leading complex cross-functional (XFN) technical initiatives and communicating technical concepts to internal and external partners Development experience in languages like Python, Java, Go, Rust, C/C++. (at least one) Experience with generative AI tool stacks including LLMs such as LLaMA, GPT, Claude, etc Experience working with external partners, customers, or stakeholders to understand their technical requirements and deliver solutions Experience with cloud-based technologies, APIs, and data integration
