Engineering Fellowship
Core
Apply technical skills to support high-impact research problems in AI safety, threat intelligence, and red teaming, working across the project lifecycle from data processing to model deployment.
Role type
Engineering Fellow (Software Engineering, Data Engineering, or Machine Learning)
Builds
Cloud infrastructure, data pipelines, visualizations, and sophisticated ML models for frontier AI labs and security teams
Domain
AI Safety, Threat Intelligence, Red Teaming, Cloud Infrastructure
Deliverable
production ML models | product features | dashboards & analysis | infrastructure
Required skills
Python, quantitative foundation, cloud infrastructure design, data architecture, ML model training/evaluation, agentic systems, RAG, AI agent frameworks
Preferred skills
Google Cloud Platform, web scraping/crawling, computer vision, MLOps tools, multimodal learning
Technologies
Python, Cloud Storage, CloudSQL, Cloud Spanner, Cloud Composer, Airflow, Cloud Run, Pub/Sub, Vertex AI, Compute Engine, Beautiful Soup, Selenium, Scrapy, Docker, Kubernetes, CI/CD, MLflow, LangChain, LlamaIndex, OpenAI Agents, AutoGen
Responsibilities
Collaborate with engineers on client-facing products and in-house tooling; Research experiment design and automation for abuse detection or red teaming; Ideate new research approaches in Trust & Safety and AI Security; Implement cloud infrastructure for deploying ML models; Source, curate, and process diverse data sources; Train, validate, evaluate, and deploy cutting-edge ML algorithms including classifiers, LLMs, and computer vision models
Seniority
Early-career to mid-level, hands-on IC
