5 months ago
Washington, DC, USAEntry Level
Responsibilities
- Collaborate with engineers on client-facing products and in-house tooling
- Research experiment design and automation related to abuse detection and AI red teaming
- Develop research approaches to Trust & Safety and AI Security problems
- Implement cloud infrastructure for deploying machine learning models
- Write high-coverage test suites and apply software engineering practices
- Source, curate, and process diverse data, including internet-scale datasets
- Design data architectures, production data storage, custom APIs, dashboards, and visualizations
- Train, validate, evaluate, and deploy machine learning algorithms, LLMs, and computer vision models
- Build agentic systems for automated prompting, red teaming, research, and experimentation
- Support other critical initiatives
Requirements
- Strong academic background and quantitative foundation demonstrated through applied coursework, research, or hands-on experience
- Strong Python background
- Ability to communicate technical concepts clearly to non-technical audiences
- Software Engineering concentration candidates should have experience designing and building end-to-end backend systems and proficiency in languages such as Python, Java, Kotlin, Node.js, or Go
- Software Engineering concentration candidates should understand secure systems, APIs, microservices, authentication, encryption, secure API development, and attack mitigation
- Data Engineering concentration candidates should have experience with web scraping or crawling tools such as Beautiful Soup, Selenium, or Scrapy
- Machine Learning Engineering concentration candidates should have computer vision skills, familiarity with multimodal learning or cross-domain model evaluation, and exposure to MLOps tools and practices
- Machine Learning Engineering concentration candidates should understand retrieval-augmented generation, AI agent frameworks, and context-aware orchestration tools such as LangChain, LlamaIndex, OpenAI Agents, or AutoGen
- Familiarity with Google Cloud Platform or similar cloud, storage, database, workflow orchestration, and machine learning services is preferred
- Experience managing projects from design through deployment is preferred
Benefits
- Flexible start and end dates
- Remote work from the continental U.S.
- Flexible schedule of up to 20 hours per week, negotiable
- Hourly pay commensurate with experience and qualifications
- The fellowship offers $30 per hour for undergraduate students, $35 per hour for graduate students, $50 per hour for advanced PhD students, $60 per hour for postdocs or non-tenured positions, and $125 per hour for tenure-track academics
Tech Stack
Categories
About 10a Labs
10a Labs provides AI security and threat-intelligence services for organizations deploying advanced models, including red teaming, model evaluations, and intelligence collection. It sells to engineering, safety, and security teams at frontier AI labs and large technology platforms, including Fortune 10 companies. The company is privately held and focuses on assessing AI infrastructure risks and classification systems for enterprise customers.