Software and machine learning engineer
I build reliable data and ML systems, developer tools, and infrastructure.
Boston, MA
Selected tools and systems I design, build, and maintain.
A job execution platform with daemonless local operation and an optional shared control plane for durable background work, scheduling, retries, logs, and failure analysis.
Engineering focus
Built around transactional state transitions, concurrent coordination, cross-platform process control, and explicit failure recovery.
A Python toolkit for running reproducible benchmark matrices, collecting repeated measurements, and detecting performance regressions.
Engineering focus
Treats performance testing as an experiment, with paired designs, evidence thresholds, statistical comparisons, and machine-readable reports.
An opinionated project generator that creates production-ready Python package repositories from a short interactive questionnaire.
Engineering focus
Generated projects include typed source layouts, tests, documentation, security checks, packaging, containers, CI, and release automation.
Architecture notes and technical deep dives on data systems, performance, machine learning, and developer tools.
How benchmatrix turns pytest-benchmark timings into paired, matrix-aware, statistically explicit, and auditable performance regression decisions.
How Jobman controls process trees across platforms, enforces cancellation and timeouts, and records output without confusing log integrity with process outcome.
Python Project Foundry generates production-ready Python repositories with testing, documentation, security, CI, containers, and releases built in.
Production-minded engineering across data, ML, and infrastructure.
01
I build data pipelines, model workflows, and evaluation systems with Spark, Airflow, SQL, and cloud infrastructure.
02
I design maintainable Python and Go software with typed interfaces, automated tests, and CI.
03
I build tooling for long-running workloads, reproducible environments, observability, and release automation.
Reach out about software engineering or ML/AI engineering roles, or to discuss data systems and developer infrastructure.