Engineering Fellowship

About the role

This role is for an Engineering Fellow who will apply their 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.

Requirements

• Strong academic background and quantitative foundation demonstrated through applied coursework, research, or hands-on-experience
• 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, Compute Engine)
• Experience managing full lifecycle projects from design to deployment
• Software Engineering 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
• Data Engineering Experience with web scraping/crawling (e.g., Beautiful Soup, Selenium, Scrapy)
• Machine Learning Engineering
• 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

Benefits

• Flexible start / end dates
• Remote work (based in the continental U.S.)
• Flexible schedule, up to 20 hours per week (negotiable)
• Hourly pay commensurate with experience and qualifications
• $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
• $125 per hour for tenure-track academics