Applied AI Data Scientist
AE Studio (AE.STUDIO) is a bootstrapped software studio founded in 2016 that combines frontier AI alignment research with high-stakes production AI engineering. The team of 150 senior professionals builds AI-native products, custom ML models, and internal AI systems for enterprise, PE/portfolio, mid-market, and startup clients across industries like aviation, edtech, medical devices, and manufacturing.
Projects
About AE Studio
AE Studio operates as an applied AI and software engineering firm that ships production AI systems for clients while also conducting frontier alignment research in collaboration with organizations like DARPA and Anthropic. Bootstrapped since 2016 with no outside investors, the company emphasizes independence that allows it to fund alignment research and select projects it believes in. Its client work spans building AI-native products, custom machine learning models, agentic automations, evals and red-teaming, observability tooling, and knowledge graphs, delivered by senior pods embedded directly with client teams. Notable projects include pricing and marketing AI for Azul Airlines, an AI-native learning platform for Alpha School, production software for Blackrock Neurotech's brain-computer interface, and AI document ingestion automation for Global Shop Solutions. The company serves a range of clients including large enterprises navigating procurement and architecture review, private equity portfolios seeking value creation, mid-market businesses focused on operations and margins, and startups needing founder-level velocity.
Skills
About the Role
You'll work on a mix of client projects and internal research initiatives, solving real-world problems and helping build meaningful products. You'll build data-driven solutions, leverage machine learning models, and use your creativity to deliver results that matter. Beyond client work, you'll have the opportunity to propose and pursue high-impact research projects, especially those aligned with the mission of increasing agency, and promising projects could even become prioritized skunkworks initiatives.
Requirements
- Fluency in Python
- Experience with LLM lifecycle: prompt design/engineering, prompting techniques (RAG, few-shot, CoT, etc.), vector databases, multimodality, fine-tuning, and evaluation
- Proven data science experience delivering results with real-life outcomes
- Statistical & causal ML fundamentals: experimental design, uncertainty quantification, and rigorous model evaluation across tabular, time-series, and foundation-model fine-tuning tasks
- Deep learning experience building/training NLP or computer vision models with PyTorch, TensorFlow, or JAX
- Experience with Agile & AI-powered development using lean Kanban/Scrum cycles and AI-powered tools like Cursor
- Growth mindset
- Self-management and ability to work independently
- Product and UX understanding
- Effective communication in English
Responsibilities
- Work on a mix of client projects and internal research initiatives
- Build data-driven solutions and leverage machine learning models
- Propose and pursue high-impact research projects
- Contribute to AI alignment research
- Manage client relationships and deliver results
Benefits
- Remote-first culture
- Flexible schedules
- Diversified employee equity program
- Health insurance
- Free lunches (at the office)
- Weekly knowledge-sharing talks
- Annual team retreat
- Equity in client projects and Skunkworks ventures