Founding Lead AI Engineer — Total Values
Total Values · Remote
About Us Total Values compares the impact of any investment or grant and builds portfolios optimized for goals beyond risk-adjusted return. If we get this right, we change how trillions in capital get allocated by tapping into values that investors already care about but have never been able to quantify credibly and act on. Backed by UChicago and beginning pilots with our first foundation partners. (totalvalues.io)
The Role We're looking for a founding AI engineer to own the technical vision (currently built by founder) and the core platform. This is a ground-floor role with significant equity and direct influence on a product designed to help allocators make better predictions and decisions about where capital can do the most good.
What You'd Build
- Evidence synthesis pipeline: mapping activities to peer-reviewed literature, extracting effect sizes, handling missing data and conflicting studies, regardless of what recipients report
- Impact forecasting engine: generating comparable estimates across heterogeneous investments and grants on 200+ metrics using the latest causal inference and predictive modeling techniques
- Portfolio optimization: multi-objective optimization across impact and financial goals, integrating externalities into capital market assumptions
- End-to-end AI workflows: designing, deploying, and iterating on production ML systems, not just prototypes
What We're Looking For
- Strong AI engineering background. You've built and deployed ML workflows end-to-end, not just trained models
- Experience with the latest techniques in causal inference (treatment effects, synthetic controls, Bayesian hierarchical models) and predictive modeling
- Strong Python. Production experience with data pipelines, APIs (FastAPI/Flask), and deployed applications
- Comfort with ambiguity and messy data. You've worked with real-world datasets where nothing is clean
- Thoughtful integration of AI tools into workflow to improve both speed AND quality
- Mission alignment. You believe that if we make impact measurable at institutional scale, we can fundamentally shift how capital flows in society
Nice to Have
- Experience in impact measurement, development economics, health economics, or climate modeling
- Familiarity with portfolio theory, optimization, or quantitative finance
- Open source contributions to tools like PyMC, CausalML, EconML, or similar
- Published research or competition results (DrivenData, Kaggle)
Details
- Stage: Pre-seed, backed by UChicago (Rustandy Center, Tarrson Fellowship)
- Location: Remote or Chicago
- Comp: Below-market base + meaningful founding equity
- Also open to part-time arrangements
Apply — send resume (or LinkedIn) and statement of interest to founder: [email protected]
