Scientist

5 days ago

Bangalore, India Cyble Full time

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. 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. 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.). 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. 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 . Research mindset—demonstrated by papers, GitHub, patents, or strong experimentation projects. 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: : Remote (India / Asia)

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