Artificial Intelligence Scientist

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