Cameron Pfiffer is a Founding Developer Relations Engineer in San Francisco with eight years of experience building developer-facing AI systems and probabilistic modeling tools. He leads devrel at Letta, helping teams assemble agent systems with memory — interns have dubbed him an "erector of tomorrow's cognition machines" — and previously focused on getting language models to produce predictable, structured outputs at .txt. His research-to-production background is rooted in rigorous applied statistics: as a Stanford postdoc he engineered high-performance probabilistic models on 18 TB of data, sped up inference for insurance-market analysis 3–4x, and contributed infrastructure used in auction research published in a top economics journal. A longtime contributor to the Turing.jl probabilistic programming project, he’s improved documentation, build tooling and compiler code, demonstrating a blend of deep probabilistic knowledge and practical usability-focused engineering.
Bayesian inference with probabilistic programming.
Role in this project:
Back-end Developer & Technical Writer
Contributions:7 releases, 55 reviews, 302 commits in 2 years 7 months
Contributions summary:Cameron's contributions primarily revolved around the documentation and build processes of the Turing.jl project, which is a probabilistic programming language. Their work included migrating the documentation to Documenter.jl, refactoring build scripts, and updating links. They were also involved in small-scale refactoring within the compiler and addressing packaging notations.
Contributions:108 commits, 108 pushes, 1 branch in 5 years 5 months
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