10a Labs is looking to solve AI safety and security challenges by detecting abuse at scale and delivering state-of-the-art red teaming across high-impact security and safety challenges.
Requirements
- Strong analytical toolkit (Python, SQL, Jupyter, scikit-learn, Pandas, etc.)
- Familiarity with modern ML tooling (e.g., PyTorch, Hugging Face, LangChain)
- Experience working with LLMs and embedding-based classification systems
- Background in data science, applied ML, or ML engineering, with proven experience in production-grade systems
- Experience with open-source model evaluation tools (Promptfoo, DeepEval, etc.)
- Safety evaluation, red teaming, or adversarial content testing in LLMs
- Trust & safety or risk-focused classification systems
Responsibilities
- Design the technical implementation of a robust red teaming project.
- Lead adversarial testing efforts (e.g., red teaming, evasion probes, jailbreak simulation) and analysis efforts.
- Work with researchers and domain experts to define labeling schemas and edge-case tests.
- Partner with ML and infrastructure engineers to ensure production readiness, observability, and performance targets.
- Automate red teaming, including developing automated workflows for prompt generation, model evaluation, and execution of AI experiments; fine-tune LLMs or classification systems.
- Brainstorm novel research approaches to both known and emerging problems involving AI, data, and the internet.
- Communicate technical strategy and tradeoffs clearly across internal and client teams.
Other
- Degree (or equivalent work experience) in Data Science, Information Science, Computer Science with ML focus, or a related field (graduate degree preferred)
- Excellent communication skills across strategy and technical domains
- Comfort working in fast-moving, high-impact environments, such as startups, AI research labs, or security-focused teams
- 3-5 years of experience in applied data science, ML product work, or security-focused AI, including technical leadership or staff-level ownership
- U.S.-based, fully remote work environment
