Matthew Marshall

• Architect and principal author of aion (~6,200 of 6,450 commits), a declarative, multi-tenant application platform where AI agents are first-class participants under machine-checked contracts, together with the build and deploy substrate it runs on.6,200 commits
• Mechanized the normative specification in Lean 4: a 57-RFC suite reduced to a seven-proposition kernel, with 1,400+ machine-checked theorems across 570 modules covering permission algebra, bitemporal CRDT convergence, safe schema migration, and typed-expression soundness. Proofs run as Bazel test targets, so a spec regression fails CI like any other test.1,400+ proofs
• Authored rules_lora, Bazel-native LoRA fine-tuning: typed SFT datasets validated at build time, declarative torchtune/peft recipes, a RunPod H100 backend, and an ExpertManifest routing contract, plus a Rust/candle adapter merge validated byte-exact against peft for two-stage fluency-rebase training. Trained a Qwen2.5-1.5B NL-to-BGP parser and an 8-dimensional box embedding for schema.org grounding.mAP 0.982
• Stood up a self-hosted Buildbarn remote-execution and cache plane: cold clone to built in 175 s (vs. ~48-min GitHub Actions baseline), two bzlmod registries serving 100+ rules_* modules behind machine-checked conformance gates, blast-radius-scoped test selection as the merge gate, and SOC 2 evidence emitted as a control-plane byproduct.175 s
• Led SAVVI's first external customer APIs — employer setup and Data Service Interface endpoints — extending OAuth2 to M2M clients and building JSON-Schema tooling to migrate models to Pydantic, with generated schemas backing contract and snapshot test suites.

• Led the development of a microservices-based portfolio benchmarking engine using gRPC and Protobuf, supporting arbitrarily complex composite index calculations, real-time FX conversion, and flexible fund performance comparisons.

• Directed NSF-funded R&D as PI for two grants (1722276 and 1927042) focused on using symbolic AI and optimization to address climate-based financial risk management. Managed personnel, budgets, timelines, and reporting requirements.2 grants
• Optimized geospatial clustering algorithm for reinsurance customer, significantly reducing O(n2) runtime complexity for distance matrix calculations by using H3 as a discrete global grid system and parallelizing with TensorFlow.O(n²)

• Advised data engineering team for 2 years at unicorn alternative protein company on data pipeline design in GCP.
• Developed serverless ETL in AWS Lambda for forensic accounting system, analyzing 30M transactions in PostgreSQL.
• Led design and implementation of iOS mHealth app and web portal for nutritionist telehealth platform.

• Engineered performance and query enhancements for portfolio compliance alerts with 3x speed improvement.
• Fixed numerous bugs and stability/performance issues in the IMS C# and Java codebases.
• Greatly expanded unit and integration tests and improved code coverage, quality, and documentation.

• Designed integration testing and quality metrics for critical parts of the fund subscription and redemption processes.
• Deployed automated remote code coverage and instrumentation using WMI on Windows Server.
• Coordinated and led university programming competition; designed and implemented recruitment portal.

Undergraduate research culminated with the development of a mobile app for creating labeled reinforcement learning datasets for wearable sensor data. The app let the user adjust the position of a stylized stick figure so that the activity sensor data could be properly classified. This project preceded the mobile era and was written for Windows CE using several custom graphics libraries and toolkits. Activities: MIT Football, Lambda Chi Alpha.