Job Description

Job Description

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 .

Job Tags

Similar Jobs