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# Senior Software Engineer - AI for Security, Data/Application

- **Company:** BYTEDANCE INC.
- **Location:** San Jose, CA, United States
- **Experience:** Expert
- **Salary:** $156,000
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, C++ (Programming Language), Computer Programming, Data Structures, Python (Programming Language), Machine Learning, Retrieval-Augmented Generation, Large Language Models, Information Technology, Vulnerability Analysis
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25304_59d571ca793c9e7c2a8867f7ba64d93b

## About the Role

* Strong coding and algorithm foundation: Excellent programming skills, strong knowledge of data structures and algorithms, and proficiency in at least one mainstream programming language (e.g., Python, Java, C++).
 * Familiarity with AI-related tech stack: Solid understanding of NLP, CV, ML technologies, with in-depth knowledge of LLM-related stacks (e.g., Reward Model, GRPO/PPO/DPO, SFT/RFT, CT, PE).
 * Excellent problem-solving skills: Strong analytical and problem-solving capabilities with the ability to independently explore innovative solutions.
 * Strong communication and collaboration skills: Ability to work closely with team members, explore new technologies collaboratively, and drive technological advancements., * Published research papers in mainstream conferences/journals in CV/NLP/Security domain.
 * Experience with security-related models (e.g., vulnerability detection models, malicious code analysis models).
 * Leading impactful projects or publishing significant papers in the LLM or AI security domain.

## Description

* Build and refine AI security datasets: Design and develop comprehensive, in-depth, and challenging datasets for AI-for-Security across different security scenarios.
 * Explore model consistency and performance prediction in security contexts: Conduct deep research on LLM performance during training on security tasks and assess the performance limits of models in security applications.
 * Develop security data and evaluation standards from an interpretability perspective: Propose interpretability-based standards grounded in model mechanisms to assess transparency and reliability of LLMs in security decision-making and remediation.
 * Red Teaming and model optimization: Perform Red Teaming from an evaluation perspective to systematically identify weaknesses of LLMs in security contexts and propose targeted optimization strategies.
 * Build RAG evaluation systems: Design end-to-end evaluation metrics and benchmarks for security-specific RAG systems, create automated evaluation workflows, and develop interpretability and traceability tools for RAG systems., Qualified applicants with arrest or conviction records will be considered in accordance with federal, state, and local laws. Positions involving the following duties may require a conditional offer or withdrawal:
 * Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
 * Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems;
 * Exercising sound judgment.