Character & Simulation TA / Applied-AI Engineer
For 25 years I've rigged and simulated digital characters for feature film and AAA games, from The Matrix to World of Warcraft. Today I build applied-AI agents and the evaluation systems that prove they hold up.
Most of those years I led the work as well as doing it: the Avatar Hair team at Meta, seven years as Rigging & Simulation Lead on Blizzard cinematics, and a CharacterFX team of 25+ at DreamWorks. The job was always systems rather than shots, one rig or solver that has to hold up across an entire slate of characters.
Simulation teaches one lesson that transfers completely: a result can look right and still be wrong. A cloth sim that reads perfectly in one frame can be broken in every other. Agentic and generative systems fail the same way, plausibly. So I build agent systems and retrieval pipelines together with the evaluation harnesses that prove they still work.
My specialty: the evaluation harnesses that make agent systems improvable rather than merely impressive. At Meta I hardened a 50+-user deep research swarm agent with a 15-question scoring matrix: 200+ full rounds of measure, fix, re-score. I also deployed devserver task loops that wrote their own self-improving skills, and team project frameworks pairing engineers with OpenClaw in one shared cloud workspace.
An independently authored realtime runtime for Hermes Agent on LiveKit: conversation stays responsive while real work continues. Speech in the foreground, tasks in the background, separate cancellation scopes so interrupting a sentence never kills the work behind it. Interrupted or stale playback is never counted as heard. Experimental.
Architecture noteA UE 5.8 project where one skeleton-agnostic Animation Blueprint Template drives a roster of differently-proportioned rigs. The original layer is verification: every rig's graph is golden-diffed against a reviewed baseline and asserted per commit, with live per-node blend-weight introspection. Authoring composes the open-source monolith server.
Architecture notemainframe-mcp, a 100% local, GPU-accelerated knowledge server: Qwen3 embeddings with a native Qwen3 reranker, hybrid search, and ambient memory with conflict-aware consolidation. Its in-repo eval harness measured +26% / +33% retrieval gains.
Architecture noteclaude-oracle, a multi-tier research orchestrator. Parallel Haiku scouts fan out breadth-first, a Sonnet tier synthesizes, and one briefing comes back to the session: roughly 10x the research breadth at a fraction of the cost. MIT-licensed.
Architecture noteProblems single agents never hit. vram-mcp lets agents share one NVIDIA GPU: TTL claims, real busy detection via NVML, protected eviction. hardline-mcp gives local Claude Code, Codex and Hermes agents a durable mailbox.
Architecture noteA FLUX.2 LoRA that grows a full 94-character typeface from a two-glyph reference, vectorizes it into real Bézier outlines and ships an installable OTF and WOFF2. Candidates are picked by a four-metric harness, one of which I had to build.
Architecture noteSeven repositories are public on GitHub. Much of the rest lives behind NDAs: agentic pipelines and physics-ML training data at Meta, plus several private production systems. Glad to walk through any of it in depth.
Real-time avatar systems
Avatars & Horizon Meta Reality Labs · 2022–2026
Built the core avatar rigging and deformation systems in a production real-time VR/mobile engine: auto-rigging, autofit deformation, skinning, blendshapes and skeleton standardization, plus node-graph clothing-rig automation and runtime animation & simulation graphs, all inside hard VR and mobile performance budgets. Lead of the Avatar Hair team. Delivered 100 character rigs used to train a physics-based ML rigging model.
Rigging & Simulation Lead
Blizzard cinematics Blizzard Entertainment · 2015–2022
Full character rigging (full-body, facial, muscle, clothing and hair) across World of Warcraft, Overwatch, Diablo, Heroes of the Storm and Hearthstone. Architected the simulation branch of the studio’s modular, graph-based rig-build system and the PyQt tooling around it, and owned rigging and shot simulation on 25+ cinematics.
CharacterFX Lead
Eight feature animations DreamWorks Animation · 2005–2015
Led a CharacterFX team of 25+ while staying hands-on with hero-character cloth, hair and skin across How to Train Your Dragon, Kung Fu Panda, Puss in Boots, Bee Movie, Over the Hedge, Turbo, Penguins of Madagascar and Home. Pioneered cloth-based skin solvers for hero characters, and wrote many of the department’s core Python tools.
Autonomous crowd agents
The Chronicles of Narnia Rhythm & Hues Studios · 2004–2005
Motion editing for the autonomous crowd agents on The Lion, the Witch and the Wardrobe, plus motion-capture TD work.
Digital-human facial capture
The Matrix sequels ESC Entertainment · 2002–2004
Facial rigging, sculpting, match-move and texture projection on the Universal Capture system behind Reloaded and Revolutions, and part of the team behind that award-winning system. Primary contributor to “Making of The Superpunch”, the piece screened at the SIGGRAPH 2004 Electronic Theater.