makermaker.ai

makermaker.ai builds autonomous research agents for recursive self-improvement, specifically multi-agent systems designed to propose, run, and analyze machine learning experiments. The company serves the artificial intelligence and machine learning research sector by developing systems that bridge research and production, focusing on model efficiency, training infrastructure, evaluation tooling, and deployment pipelines.

In the domain of artificial intelligence and machine learning, makermaker.ai investigates and implements efficient inference and training methods such as quantization, speculative decoding, sparse and structured attention, distillation, and mixture-of-experts inference. The work requires designing algorithms, conducting controlled experiments at production scale, and translating research code into reliable infrastructure that supports data pipelines, observability, and distributed training systems.

The open roles indicate that makermaker.ai is building small, senior-level teams across research and machine learning engineering. The current open positions include a Researcher for Efficient Inference and a Machine Learning Engineer (General). These roles are located in San Francisco and are strictly on-site positions, requiring candidates with 5 to 6 or more years of hands-on experience in machine learning research or production-grade ML systems.