Source: Paraform - https://www.paraform.com/share/neocognition/cmpejiwh000020cjykwkd1wy3
Compensation: $280,000-$350,000 base + competitive equity (likely 0.05%-0.5%).
Location: Palo Alto, CA - on-site 5 days/week; relocation supported; fully remote only for truly exceptional candidates. Visa: open to transfers and most visas; sponsorship for strong candidates willing to relocate.
About this role
As a Member of Technical Staff [Research] at NeoCognition, you'll be part of the core team advancing the frontier of LLM agents: systems that can reason, plan, and act reliably in the real world. You'll lead end-to-end research projects, from conceptualization and experimentation to building and testing product prototypes, working closely with engineers and designers.
Responsibilities
Lead research initiatives in LLM reasoning, post-training, and agentic system design
Develop new methods to improve capability, reliability, and safety of autonomous LLM agents in real-world environments
Collaborate with software and platform engineers to prototype and productionize research outcomes into sticky product experiences
Design and execute experiments, benchmark performance, and analyze model behaviors to identify failure modes and opportunities
Stay abreast of reasoning, multi-agent systems, RLHF, tool use and LLM fine-tuning; contribute to publications or open source where appropriate
Help shape the research culture and technical roadmap as an early team member
Tech stack
Python, PyTorch, JAX, TensorFlow, LLMs, RLHF, Llama, Mistral, Open-weight models, Post-training, Agentic system design, Multi-agent systems, AI coding tools
About NeoCognition
AI agent lab for specialized intelligence, developing AI agents that continuously learn to reach expert-level intelligence. Founding team's research is used in frontier models from OpenAI, Anthropic, Google and others. 10 employees, founded 2025, $40M total funding, Palo Alto.
2+ years of LLM research (agents, post-training, or evaluations) with publications
Hands-on with post-training (instruction tuning, RL, reasoning), RLHF and open-weight models
Python; PyTorch, JAX or TensorFlow
On-site 5 days/week in Palo Alto (relocation supported)