Engineering Fellowship

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.

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 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

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