Applied AI Research Scientist - Agent Systems & RL

Human Capitalists

United States

Presencial

USD 180 000 - 240 000

Tempo integral

Há 5 dias
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Resumo da oferta

Human Capitalists is seeking a senior AI researcher to build the core agent behavior for a revenue-focused AI system, guiding from hypothesis to production. You will lead hands-on development of agent harnesses, tool use, and multi-step reasoning within a fast-moving team.

You will design and evaluate experiments, contribute to publications when possible, and collaborate with a US-based leadership group across time zones to push research toward production-ready solutions.

Qualificações

  • MS or PhD in Computer Science, Mathematics, Statistics, or another quantitative discipline.
  • 5+ years of experience in applied AI research or applied science, at a senior level.
  • Hands-on experience building and improving agentic systems and agent harnesses, including tool use, multi-step reasoning, and context management.
  • Hands-on experience with LLMs or large-scale deep learning systems, including training, fine-tuning, and RLHF.
  • Understanding why models behave the way they do, not just how to use them.
  • Experience designing eval datasets or frameworks, esp. for tasks without clean ground truth.
  • Proven ability to scope and drive ambiguous research with minimal guidance.
  • Publications at top-tier venues preferred.
  • Comfortable working with a US-based leadership team across time zones.

Conhecimentos

Agentic systems
LLM experience
Large-scale DL
Reasoning and context management
Research leadership

Formação académica

MS or PhD in CS/Math/Stats or quantitative field

Descrição da oferta de emprego

Human Capitalists is seeking a senior AI researcher to build the core agent behavior for a revenue-focused AI system, guiding from hypothesis to production. You will lead hands-on development of agent harnesses, tool use, and multi-step reasoning within a fast-moving team.

You will design and evaluate experiments, contribute to publications when possible, and collaborate with a US-based leadership group across time zones to push research toward production-ready solutions.

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