Are you passionate about Generative AI and want to apply it to one of the most impactful domains — cybersecurity?
Join our cutting-edge startup in the San Francisco Bay Area, where we are developing AI systems that transform how organizations understand, detect, and respond to cyber threats.
As an Applied AI Scientist, you'll bridge AI research and real-world cybersecurity use cases — designing, implementing, and optimizing models that extract, reason, and act on complex security data.
You'll work closely with cybersecurity experts, AI infrastructure engineers, and stakeholders to build end-to-end GenAI solutions: from concept to deployment.
This role blends deep applied research with practical engineering, ideal for someone eager to push the limits of Generative AI for meaningful impact.
Why Join Us:
• $25M Seed Funding: Strong capital foundation to innovate and scale fast.
• Early Success: Trusted by Fortune 500 companies, validating real-world demand.
• Experienced Leadership: Founders with 25+ years in cybersecurity — previous ventures valued at $3B+.
• Elite AI Leadership: Heads of AI, Engineering, and Product from world-class tech companies.
• Advanced AI Stack: LLMs, embeddings, RAG systems, LangGraph orchestration, and multimodal AI.
• Competitive Compensation: Excellent salary, meaningful equity, and room for technical leadership growth.
• Cybersecurity Knowledge Preferred but Not Required: We'll teach you the domain — you bring the AI innovation.
Key Responsibilities:
Core Applied AI Research
• Collaborate with cybersecurity researchers and stakeholders to scope AI-driven solutions to security problems (e.g., vulnerability management, code analysis, threat detection).
• Conduct applied research using the latest LLMs and embedding models (Claude, Google GenAI, Unsloth, vLLM).
• Prototype, fine-tune, and evaluate GenAI and RAG/CAG architectures for classification, summarization, reasoning, and context synthesis.
• Perform embedding-level optimization for text, code, and image data using Unsloth, Hugging Face, Voyage, or similar frameworks.
System Development & Integration
• Develop and test end-to-end AI pipelines integrating Milvus or Pinecone for semantic retrieval.
• Build agentic AI systems using LangGraph or similar frameworks to enable autonomous reasoning and task chaining.
• Collaborate with MLOps engineers to deploy and monitor AI models in production securely and efficiently.
• Contribute to synthetic data generation pipelines for fine-tuning and evaluation.
Evaluation & Optimization
• Implement evaluation frameworks using DeepEval and GenAI tools (Claude / Google GenAI) for factuality, reliability, and robustness.
• Optimize model performance across latency, accuracy, and cost using vLLM, quantization, or caching strategies.
• Maintain reproducible experiment tracking with MLflow, Weights & Biases, or internal tools.
Innovation & Leadership
• Stay ahead of GenAI trends — multi-modal reasoning, agentic orchestration, embedding adaptation.
• Explore hybrid LLM deployment strategies (local Unsloth/vLLM + cloud APIs like Claude, Google GenAI).
• Document best practices, share learnings, and mentor junior scientists on applied GenAI workflows.
Qualifications:
Required
• 4+ years in Applied AI / Machine Learning Research / Data Science.
• Strong understanding of LLMs, embeddings, RAG systems, and multimodal learning.
• Proficiency in Python and frameworks like PyTorch, Transformers, Hugging Face, or LangChain.
• Experience in prompt engineering, model evaluation, and retrieval-based reasoning.
• Hands-on experience with vector databases (Milvus / Pinecone) and orchestration frameworks (LangGraph / LangChain).
• Strong communication skills and ability to collaborate across research and engineering functions.
Preferred
• Experience with fine-tuning LLMs or embeddings using Unsloth or similar frameworks.
• Familiarity with Claude / Google GenAI APIs for cloud-based inference and evaluation.
• Exposure to cybersecurity or enterprise data (CVEs, pluginText, network or asset logs).
• Prior work on synthetic data generation and evaluation frameworks (DeepEval).
• Experience in a fast-paced startup or applied research environment.
Our Culture & Team
• Collaborative and Mission-Driven: Every project directly advances global cybersecurity.
• World-Class Mentorship: Work with senior experts from top AI and security companies.
• Growth-Oriented: Opportunities to lead GenAI initiatives and own major research tracks.
• Inclusive and Innovative: We value diverse perspectives and open experimentation.
Perks & Benefits
• Comprehensive medical, dental, and vision coverage.
• Wellness and professional development stipends.
• Equity options — your impact equals ownership.
• Access to state-of-the-art GPUs, APIs, and GenAI frameworks.
