Engineering Fellowship

About 10a Labs: 10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely. About the role: As an Engineering Fellow, you will apply your technical skills to support high-impact research problems. Fellows will contribute across the project lifecycle — from processing diverse data sources and designing dynamic visualizations, to deploying sophisticated models and building cloud infrastructure. This is a hands-on role at the intersection of applied research and practical engineering, with opportunities to explore novel methods, test ideas quickly, and generate insights. Fellows specialize in one of three concentrations based on interest and past experience: Software Engineering, Data Engineering, or Machine Learning. In this role, you will: Collaborate with engineers on real projects, including client-facing products and in-house tooling; Assist with researching experiment design and automation, particularly as it relates to abuse detection or red teaming of AI systems; Ideate / brainstorm new research approaches to known and novel problems in the Trust & Safety and AI Security fields; and Sup [... source excerpt omitted ...] and Guiding project development with software engineering best practices, including version control, continuous integration, and design patterns. Data Engineering concentration responsibilities may include: Sourcing, curating, and processing diverse data sources across domains and modalities, including automated collection of internet-scale datasets; Designing data architecture schemata, implementing with production-grade data storage tools, and interfacing via custom APIs; and Developing front-end dashboards and other visualizations. Machine Learning concentration responsibilities may include: Training, validating, evaluating, and deploying cutting-edge machine learning algor [... source excerpt omitted ...] early to both technical and non-technical audiences; and Is excited about contributing to real-world applications and exploring new methods that push beyond standard benchmarks. Requirements: Strong academic background and quantitative foundation demonstrated through applied coursework, research, or hands-on-experience Strong Python background Clear communicator of technical concepts for non-technical audiences Nice to have: Familiarity with Google Cloud Platform (or similar), including storage and database services (e.g., Cloud Storage, CloudSQL, Cloud Spanner), workflow orchestration (e.g., Cloud Composer/Airflow, Cloud Run, Pub/Sub), and ML services (e.g., Vertex AI, Comput