Technical Lead (Applied Data Scientist)

10a Labs (Headquarters: Remote (US))

Python LLMs transformers cybersec AI Safety Red Teaming Threat Detection Data Science Leadership Statistics Machine Learning Data Science Staff Engineer Management

**About 10a Labs:**
10a Labs is building next-gen tools for LLM safety, red teaming, and AI threat detection. We are a terrific team with an incredible mission focused on making AI safer.

**Role: Technical Lead (Applied Data Scientist)**
We are looking for an experienced Technical Lead / Applied Data Scientist to guide and contribute to our efforts in AI safety and threat detection. This role involves leading projects, mentoring team members, and applying advanced data science techniques to complex problems involving LLMs.

**Responsibilities:**
*   Lead the technical direction for projects focused on LLM safety, red teaming, and AI threat analysis.
*   Apply statistical analysis, machine learning, and data modeling techniques to understand and mitigate AI risks.
*   Design and implement experiments for red teaming LLMs and evaluating safety measures.
*   Mentor junior engineers and data scientists on the team.
*   Collaborate with cross-functional teams to integrate data-driven insights into our products.
*   Utilize Python, LLMs, and transformers to develop innovative solutions.
*   Communicate findings and technical concepts clearly to both technical and non-technical audiences.

**Ideal Candidate:**
*   Proven experience in a technical leadership role within data science or applied ML.
*   Strong foundation in statistics, machine learning, and data analysis.
*   Expertise in Python and relevant data science/ML libraries.
*   Experience working with LLMs and transformers is essential.
*   Background in cybersecurity or AI safety research is highly advantageous.
*   Excellent problem-solving, communication, and leadership skills.
*   Master's or PhD degree in Data Science, Computer Science, Statistics, or a related quantitative field, or equivalent experience.
*   Ability to thrive in a fast-paced, remote research and development environment.