Job description
 
                         Company Description
Cyble (YC W21) is a Series B-funded global cyber intelligence start-up supported by notable VC firms and Y Combinator.
We provide customers with AI-powered actionable threat intelligence to manage cyber risks effectively.
Our team specializes in delivering cutting-edge solutions to help organizations and governments stay ahead of cyber threats.
We’re building the next generation of memory-augmented AI systems—agents that  learn ,  recall , and  reason  like humans.
Our mission is to develop long-context AI that’s persistent, intelligent, and adaptive.
If you’re passionate about solving fundamental problems in  memory for AI , we want to hear from you.
At Cyble, you won’t just work with toy datasets or academic-scale models—you’ll be applying your ideas to  petabyte-scale real-world data , spanning global threat intelligence, telemetry, signals, and behavioral metadata.
This is your chance to build  AI memory systems at planetary scale,  work on  cutting-edge LLM and neural memory infrastructure , alongside a global team of top researchers and engineers, with direct CEO-level sponsorship.
Be at the forefront of  semantic memory, vector embeddings, and lifelong AI learning.
 As this function reports to the CEO and interfaces with our U.S.-based executive team, periodic travel to Cupertino is expected.
For high-impact contributors, relocation support may be offered to align with our long-term strategic planning efforts.
Key Responsibilities
Architect and build  semantic and neural memory systems  for large language models (LLMs) and autonomous agents.
Design memory-aware retrieval systems using  vector databases (FAISS, Milvus, LanceDB)  and  embedding models (OpenAI, Hugging Face, Cohere) .
Research and implement techniques for  episodic ,  declarative , and  procedural memory  inspired by cognitive and neuroscience principles.
Integrate long-term memory modules with  LLM stacks  (GPT, LLaMA, Claude, Mistral, etc.).
Contribute to both open-source frameworks and proprietary IP in  RAG pipelines ,  agent memory , and  knowledge grounding .
Collaborate with top-tier researchers, security analysts, and the CEO himself to shape Cyble’s strategic AI future.
Collaborate with product teams to translate research into real-world AI products used globally.
Qualifications
Bachelor’s/Master’s/PhD in CS, AI, Cognitive Science, Applied Math, or related disciplines (IITs, IISc, IIITs, BITS, top NITs preferred but not mandatory).
Strong experience with  PyTorch ,  TensorFlow , or  JAX  for building deep learning systems.
Hands-on with  semantic search ,  vector similarity , and  embedding space reasoning .
Solid grasp of LLMs and memory-augmented architectures (Transformers + Memory, RAG, kNN-augmented models, etc.).
Research mindset—demonstrated by papers, GitHub, patents, or strong experimentation projects.
Worked on LangChain, LlamaIndex, AutoGPT, or other memory-capable agent platforms.
Background in  neuroscience-inspired AI ,  knowledge graphs , or  cognitive modeling .
Strong publications or open-source visibility in AI memory systems.
Send your resume, GitHub or research portfolio, and a brief note on your work in semantic or neural memory to:  beenu@cyble.com
Location : Remote (India / Asia)
Function:  CEO – Innovations Team
 
                    
                    
Required Skill Profession
 
                     
                    
                    Computer Occupations