Now

May 2026.

Working

• Post-training harnesses for SFT, DPO, verifier scoring, and best-of-N selection.
• Telemetry retention for ML systems: logging budgets, summary interfaces, and failure analysis.
• ALife experiments: replicators, program soups, mutation search, and population traces.
• Tabular models: foundation-model baselines, uncertainty, runtime, and training dynamics.

Testing

• Evaluation signals under distribution shift.
• Benchmark design that separates model behavior from dataset fit.
• Which project repos need hosted demos, benchmark results, or just a clean README.

Open To

• Research engineering roles across data, models, evaluation, and production feedback.
• Applied research work with a concrete dataset, experiment, or system to ship.