The embodied intelligence industry is witnessing a fierce talent war, with salary levels constantly exceeding expectations. ByteDance has offered a monthly salary of $13,300 to $16,800 for senior experts in embodied intelligence operation algorithms, while the head of operation and control at a star enterprise, who graduated just a year ago, has an annual salary of $420,000, and the salary for director-level positions even approaches $1.4 million.
Algorithmic talents have become highly sought-after by major tech companies. For doctoral graduates specializing fields such as motion control and navigation, the starting salary ranges from $92,400 to $98,000. For top doctoral graduates from prestigious universities areas like vision-language model (VLM), those who have published more than 4 first-author papers in top conferences can enjoy a starting salary exceeding $140,000. To secure talents, enterprises have advanced their recruitment efforts significantly.
Tech giants like Alibaba and ByteDance begin establishing connections with doctoral students as early as their first or second year of PhD studies. Startups have even launched a policy of “full-time benefits during internships”: Promising candidates who agree to join after graduation can start their internships six months or even a year in advance, receiving the same monthly salary as full-time employees offered in campus recruitment—up to $14,000 per month. With methods such as lightning-fast interviews, high signing bonuses, personal lobbying by executives emerging one after another, it has become common for outstanding candidates to hold 20 to 30 job offers, a trend highlighted in the latest AI news.
Severe Supply-Demand Imbalance Leads to Talent Shortage
The intense talent war stems from a severe supply-demand imbalance. As an interdisciplinary field, embodied intelligence imposes extremely high requirements on talents: algorithmic talents need to possess knowledge across multiple domains, hardware engineers must understand both mechanical design and algorithm collaboration, and functional talents are required to have the ability to transfer their experience. However, the rapid rise of the industry has left talent reserves far behind, resulting in a shortage of talents across the entire chain—from algorithms and hardware to supply chain management and marketing.
Currently, the path of talent flow is clear: Algorithmic talents of motion control and navigation mainly come from autonomous driving companies, large model firms, and research departments of internet giants; VLM algorithmic talents are mostly from traditional robotics enterprises, prestigious university laboratories, and overseas companies; hardware talents are mainly recruited from relevant high-end manufacturing and robotics hardware enterprises. Teams that laid out their robotics strategies early, such as Tencent Robotics X and UBTECH, have been severely affected by talent poaching.
