From $30/yr

Engineering Fellowship

Washington D.c · United States - San Franciscomid

OtherLow-Code Developer

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Requirements Summary

Strong academic background and quantitative foundation demonstrated through applied coursework, research,

Technical Tools

OtherLow-Code Developer

~1 min read

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
Support other critical initiatives.

~1 min read

→Implementing cloud infrastructure for deploying machine learning models;
→Writing high-coverage test suites for complex codebases; and
→Guiding project development with software engineering best practices, including version control, continuous integration, and design patterns.

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→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.

~1 min read

→Training, validating, evaluating, and deploying cutting-edge machine learning algorithms including classifiers, LLMs, and computer vision models;
→Building agentic systems for automated prompting, red-teaming, research, and rapid experimentation;
→Supporting projects with specialized knowledge of frontier model architectures and cutting-edge technology.

Brings curiosity and creativity to ambiguous research problems, with a bias toward experimentation and rapid iteration;
Thrives in collaborative, interdisciplinary environments; is resourceful, proactive, and adaptable;
Is comfortable communicating technical ideas clearly 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.

~1 min read

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

~1 min read

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, Compute Engine)
Experience managing full lifecycle projects from design to deployment

- Experience designing and building end-to-end backend systems, from architecture and data modeling to deployment, scaling, and monitoring
- Proficiency in backend programming languages such as Python, Java, Kotlin, Node.js, or Go and experience building secure systems, APIs, and microservices
- Knowledge of security best practices, including authentication methods (OAuth, JWT), encryption, and secure API development; knowledge of common attack vectors (SQL injection, privilege escalation, DDoS) and effective mitigation strategies

- Experience with web scraping/crawling (e.g., Beautiful Soup, Selenium, Scrapy)

- Computer vision skills (OCR, image classification, deep fake detection)
- Familiarity with multimodal learning (text-image or text-audio) or cross-domain model evaluation
- Exposure to MLOps tools and practices (Docker, Kubernetes, CI/CD for ML, MLflow, etc.)
- Understanding of modern retrieval-augmented generation (RAG), AI agent frameworks, and context-aware orchestration (e.g., LangChain, LlamaIndex, OpenAI Agents, or AutoGen) for building intelligent applications