Research Engineer Graduate (Agentic Arch) — 2027 Start (PhD)

What you'll do

• Research agent planning, reasoning, memory, tool use, environment interaction, and multi-agent coordination; improve agents through post-training, reinforcement learning, execution feedback, search, and test-time scaling.
• Build scalable infrastructure for agent orchestration, evaluation, observability, and reliable execution; validate methods on software changes, testing, migrations, deployment, and incident response.
• Translate research into production systems, rigorously evaluate impact, and collaborate across research, infrastructure, platform, and product teams.

What they ask for

• Completing or recently completed a PhD in Computer Science or a related discipline.
• Research or engineering experience in AI agents or related areas such as LLM reasoning, reinforcement learning, program synthesis, or AI for code.
• Strong understanding of one or more relevant agent or model research areas, and strong programming and systems-building ability in at least one of Python, C++, Go, or Java.
• Ability to formulate problems, design rigorous experiments, analyze results, iterate from evidence, and collaborate effectively.

Nice to have

• Research contributions such as influential publications, open-source work, or deployed systems; relevant venues include NeurIPS, ICML, ICLR, ACL, MLSys, OSDI, SOSP, NSDI, ICSE, and FSE.
• Experience with LLM agents, AI developer tools, agent platforms, model post-training, reinforcement learning, distributed systems, developer platforms, or production operations.

Tools

Python, C++, Go, Java

AI focus

Frontier research and production deployment of reliable long-horizon agents for software engineering and operations, including planning, reasoning, memory, tool use, reinforcement learning, and agent evaluation.