Founding AI Engineer (Research & Systems)

AimHire • San Francisco Bay Area
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AI Summary

AimHire is seeking a Founding AI Engineer to lead research and implementation of core agentic models. This role requires a PhD/MSc in AI/ML with hands-on PyTorch, transformer, and RL experience. The position offers a unique opportunity to build next-generation reasoning systems for AI agents.

Key Highlights
First AI hire to own research and implementation of core agentic models.
Opportunity to work on cutting-edge AI problems like long-horizon planning and self-improving agents.
Seed-stage startup backed by Khosla Ventures and leading AI researchers.
Key Responsibilities
Own the research and implementation of core agentic models.
Turn groundbreaking research papers into robust, scalable systems.
Test ideas at scale with compute resources.
Technical Skills Required
PyTorch Transformer architectures Reinforcement Learning
Benefits & Perks
$160K - $250K Compensation
0.8% - 2.0% Equity
Visa Sponsorship Available
Nice to Have
Publication record at top conferences (NeurIPS, ICML, ICLR, ACL)
Experience with frameworks like LangChain, LangGraph, or AutoGen
Research in Multi-agent systems, RLHF, reasoning, planning, memory architectures, or program synthesis

Job Description


Title: Founding AI Engineer (Research & Systems)

Target: PhDs & Research Masters from Stanford, MIT, Berkeley, CMU focused on AI, ML, NLP, Agents.

Location: San Francisco, CA | On-Site

Compensation: $160K - $250K | 0.8% - 2.0% Equity

Visa Sponsorship: Available (H1B, OPT, F1, TN, O1)


About Us

We are a seed-stage startup, backed by Khosla Ventures and leading AI researchers, building the next generation of reasoning systems for AI agents. Our mission is to move beyond simple RAG and chain-of-thought, creating models that can dynamically plan, execute, and learn in complex environments. Our technical founder is a former Research Lead from Google DeepMind.


The Role

We are looking for our first AI hire to own the research and implementation of our core agentic models. You will be responsible for turning groundbreaking research papers into robust, scalable systems. This is a rare opportunity to work on cutting-edge problems like long-horizon planning, tool-use optimization, and self-improving agents, with the compute resources to test your ideas at scale.


Ideal Profile

  • Currently pursuing or recently completed a PhD/MSc in Computer Science, AI, or a related field.
  • Publication record at top conferences (NeurIPS, ICML, ICLR, ACL) is a huge plus.
  • Deep, hands-on experience with PyTorch, transformer architectures, and reinforcement learning.
  • Experience with frameworks like LangChain, LangGraph, or AutoGen is preferred, but a strong fundamental understanding of what they abstract is more important.
  • You read ML papers and immediately think about the implementation details and edge cases.
  • You are passionate about both theoretical rigor and shipping code that works.


Apply if you've done research in: Multi-agent systems, RLHF, reasoning, planning, memory architectures, or program synthesis.


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