7 дней назад
Research Lead (AI Agents)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Research Lead (AI Agents): Building self-improving agent systems for difficult, long-running engineering tasks across ASIC development, inference, and supercomputing with an accent on memory, context management, tool use, evaluation, and model post-training. Focus on designing research agendas, training custom models with SFT and RL, and scaling reproducible experiments across hundreds or thousands of concurrent agents.
Location: On-site in San Jose, California, United States. The role is fully in-person, and relocation support is available for candidates moving to San Jose.
Company
builds hardware, software, racks, and manufacturing systems for frontier AI inference, with a focus on throughput and latency.
What you will do
- Own the research agenda for self-improving agentic systems and prioritize the highest-impact bottlenecks.
- Work with domain engineers across ASIC development, inference, and supercomputing to understand workflows and convert agent failures into research questions.
- Develop long-running task systems covering memory, context management, tool use, planning, and multi-agent coordination.
- Build evaluations for correctness, reliability, and efficiency, and verify that improvements transfer to production.
- Train custom models with supervised fine-tuning, reinforcement learning, and distillation using execution trajectories and failure analysis.
- Scale experiments to hundreds or thousands of concurrent agents while maintaining reproducibility, observability, and compute-cost control.
Requirements
- Strong research judgment and a record of turning ambiguous problems into clear hypotheses, experiments, and useful systems.
- Excellent engineering ability across research exploration, agent experimentation, low-level debugging, and production execution.
- Experience building agents for complex, multi-step tasks involving context, memory, tools, evaluation, and failure recovery.
- Hands-on experience with LLM post-training, including supervised fine-tuning and reinforcement learning.
- Experience making meaningful progress under compute and data constraints.
- Ability to set technical direction and collaborate closely with domain experts.
Nice to have
- Experience with ASIC design or verification, accelerator kernels, inference systems, or large-scale compute infrastructure.
Culture & Benefits
- Medical, dental, and vision packages with generous premium coverage.
- $500 monthly credit for waiving medical benefits.
- $2,500 monthly housing subsidy for employees living within walking distance of the office.
- Relocation support for moves to San Jose, wellness benefits, and daily lunch and dinner at the office.
- Unlimited compute budget subject to return-on-investment justification.
- Fully in-person collaboration across research and engineering disciplines.
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