Research Intern
NeoCognition · Hybrid
MeritLog read this listing from NeoCognition's Ashby job board and last checked it on September 8, 2026.
Source: the employer's Ashby job board. Open the original listing for current details.
Job details
- Work model
- Hybrid
- Salary
- Not listed by source
- Location
- Palo Alto
Hiring context
How this role compares at NeoCognition
NeoCognition has 4 live roles in MeritLog’s catalog across 2 job families, and 2 of them are in data & analytics. 0 of those listings publish a pay range, a disclosure rate of 0%.
Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.
What the role asks for
What you'd do
- Explore novel research directions in areas such as LLM reasoning, planning, tool use, multi-agent systems, or evaluation methodologies.
- Design and execute exploratory experiments to test new hypotheses and push the boundaries of what agentic systems can do.
- Build research prototypes that demonstrate new capabilities or insights, even if they are not immediately production-ready.
- Collaborate with the research team to document findings, analyze results, and iterate on ideas.
- Work toward publishing research outcomes in top-tier AI venues (NeurIPS, ICLR, ICML, ACL, etc.) or contributing to open-source efforts.
- Participate in team discussions, paper readings, and brainstorming sessions to shape the research roadmap.
What they're asking for
- Currently pursuing or recently completed a PhD, Master's, or advanced undergraduate degree in machine learning, computer science, or a related field.Education
- Strong foundation in machine learning and natural language processing, with demonstrated interest in large language models or agentic AI systems.Skill
- Proficiency in Python and familiarity with modern ML frameworks (e.g., PyTorch, JAX, or TensorFlow).Skill
- Ability to design, implement, and analyze research experiments independently and collaboratively.Skill
- Strong written and verbal communication skills, with a passion for sharing ideas and learning from others.Skill
- Prior research experience or publications in AI, NLP, or related areas.SkillPreferred
- Experience with open-weight models, fine-tuning, or reinforcement learning.SkillPreferred
- Familiarity with agent frameworks, tool-use systems, or evaluation benchmarks.SkillPreferred
- Interest in long-term research bets and comfort with ambiguity and exploration.SkillPreferred
Parsed by MeritLog from the employer’s own posting. The full description follows below.
Job description
ABOUT THE ROLE As a Research Intern at NeoCognition, you'll explore novel ideas and work on longer-term research bets that push the boundaries of LLM agents. This internship is designed for those who want to dive deep into open research problems - from reasoning and planning to multi-agent coordination and evaluation. You'll have the freedom to pursue high-risk, high-reward directions that may not be tied to immediate product needs, but could shape the future of agentic AI systems. Your work will culminate in research prototypes and, ideally, publications that contribute to the broader AI research community. You'll collaborate closely with our research scientists and engineers, receiving mentorship and feedback as you design experiments, build prototypes, and analyze results. RESPONSIBILITIES - Explore novel research directions in areas such as LLM reasoning, planning, tool use, multi-agent systems, or evaluation methodologies. - Design and execute exploratory experiments to test new hypotheses and push the boundaries of what agentic systems can do. - Build research prototypes that demonstrate new capabilities or insights, even if they are not immediately production-ready. - Collaborate with the research team to document findings, analyze results, and iterate on ideas. - Work toward publishing research outcomes in top-tier AI venues (NeurIPS, ICLR, ICML, ACL, etc.) or contributing to open-source efforts. - Participate in team discussions, paper readings, and brainstorming sessions to shape the research roadmap. QUALIFICATIONS REQUIRED: - Currently pursuing or recently completed a PhD, Master's, or advanced undergraduate degree in machine learning, computer science, or a related field. - Strong foundation in machine learning and natural language processing, with demonstrated interest in large language models or agentic AI systems. - Proficiency in Python and familiarity with modern ML frameworks (e.g., PyTorch, JAX, or TensorFlow). - Ability to design, implement, and analyze research experiments independently and collaboratively. - Strong written and verbal communication skills, with a passion for sharing ideas and learning from others. NICE TO HAVE: - Prior research experience or publications in AI, NLP, or related areas. - Experience with open-weight models, fine-tuning, or reinforcement learning. - Familiarity with agent frameworks, tool-use systems, or evaluation benchmarks. - Interest in long-term research bets and comfort with ambiguity and exploration.