Research Engineer-Model Efficiency (AI)

Location: Singapore, Singapore; Austin, United States; or San Jose, United States

Company

hirify.global is a technology company focused on Bitcoin mining, AI cloud services, ASIC chip design, computing infrastructure, and high-performance computing datacenters.

What you will do

• Make large language models cheaper and faster to serve while preserving important quality metrics.
• Implement and adapt model-efficiency methods including quantization, sparsity and pruning, speculative decoding, MTP, serving-time attention, and KV-cache optimization.
• Develop new optimization techniques for hirify.global's models and hardware when existing methods are insufficient.
• Build rigorous evaluation practices using task-level metrics, controlled comparisons, and honest baselines.
• Validate claims about quality and throughput, including production-serving performance.

Requirements

• Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, or a related field.
• Hands-on experience with LLM inference, model optimization, or machine-learning systems.
• Strong Python programming skills and deep familiarity with PyTorch.
• Implementation-level expertise in at least one model-efficiency area, such as quantization, sparsity and pruning, speculative decoding and MTP, or serving-time attention and KV-cache methods.
• Strong understanding of transformer internals, accuracy loss in model behavior, and rigorous evaluation methodology.
• Experience with production inference or equivalent research depth; familiarity with vLLM, SGLang, or TensorRT-LLM is highly preferred.

Nice to have

• Experience with C++, CUDA, or Triton.
• Publications at top-tier systems or machine-learning venues.
• Substantial open-source contributions.

Culture & Benefits

• Inclusive environment valuing authenticity and diverse perspectives.
• Startup-style environment within a fast-growing company.
• Opportunities to contribute directly to new AI infrastructure projects and digital-asset technology.
• Autonomy, personal accountability, rapid growth, and learning opportunities.
• Training, mentoring, welfare benefits, and developmental opportunities.