Careers
Help build the platform that changes how trillions in capital get allocated.
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.
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
Map activities to peer-reviewed literature, extract effect sizes, handle missing data and conflicting studies — regardless of what recipients report.
Impact Forecasting Engine
Generate 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
Design, deploy, and iterate 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 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
Below-market base + meaningful founding equity. Also open to part-time arrangements.
Send your resume (or LinkedIn) and a brief statement of interest.
Don't see a fit?
We're always looking for exceptional people. Reach out and tell us what you'd bring.