Member of Technical Staff [Research]

NeoCognition; Palo Alto (CA); On-site; USD 120,000 - 150,000; Full time

Job summary

NeoCognition Inc. is seeking a Member of Technical Staff for research on LLM agents in Palo Alto, California. You will lead research projects and collaborate with engineers to create impactful AI systems. Essential qualifications include a solid foundation in machine learning, AI systems, and proficiency in Python along with experience in large language models. Ideal candidates also have familiarity with ML frameworks like PyTorch or TensorFlow. This is an exciting opportunity to shape the future of AI research.

Qualifications

• Strong background in machine learning, natural language processing, or AI systems, with experience in large language models.
• Deep understanding of agentic system design, LLM post-training, and data pipeline design.
• Proficiency in Python and familiarity with modern ML frameworks.

Responsibilities

• Lead research initiatives in the areas of LLM reasoning and agentic system design.
• Develop new methods to improve capability and reliability of LLM agents.
• Collaborate with engineers to prototype and productionize research outcomes.

Skills

Machine learning

Natural language processing

AI systems

Python

Reasoning

Collaboration

Tools

PyTorch

JAX

TensorFlow

Job description

About the 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. We are an AI research lab focused on making LLM agents reliable, grounded, and accessible to users, developers and enterprises.

You’ll lead end-to-end research projects — from conceptualization and experimentation to building and testing product prototypes — working closely with our engineers and designers to turn cutting-edge ideas into practical, impactful systems.

Responsibilities

• Lead research initiatives in the areas of 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 emerging work in reasoning, multi-agent systems, RLHF, tool use, and LLM fine-tuning — and contribute to publications or open-source efforts where appropriate.

• Help shape the research culture and technical roadmap of the company as an early member of the team.

Qualifications

Required

• Strong background in machine learning, natural language processing, or AI systems, with experience in large language models (LLMs).

• Deep understanding of one or more of the following areas:

  • Agentic system design (tool-use, planning, reasoning, computer-use)

  • LLM post-training (instruction tuning, RL, reasoning)

  • Data pipeline design and model evaluation

• Proficiency in Python and familiarity with modern ML frameworks (e.g., PyTorch, JAX, or TensorFlow).

• Demonstrated ability to design, execute, and analyze research experiments — from idea to implementation.

• Strong communication skills and ability to work collaboratively in a fast-paced, cross-disciplinary environment.

Nice to have

• Experience working with open-weight models (e.g., Llama, Mistral, or similar) and training infrastructure.

• Publications in top-tier AI venues (NeurIPS, ICLR, ICML, ACL, etc.).

• Prior experience building research prototypes into usable tools or products.