01
CVML enterprise annotation services
Aletheia and Tartarus evidence points to web servers, REST APIs, asynchronous workers, schema evolution, and data/model API work for annotation workflows.
2019 to 2024 · Sunnyvale, CA
Blue River Technology
Senior Software Engineer, Data and CVML Platform
Platform engineering for applied ML teams: annotation services, data lake access, workflow orchestration, and production CVML pipelines.
field to model loop
Camera, labels, lake, training, deployment.
This mockup turns the tractor image into the page signature moment: a volumetric Three.js particle object, a Deere-style sprayer tractor with visible depth, wheels, and booms that morphs into the CVML data pipeline.
1sensors
2annotation
3Athena / Databricks
4Kubeflow / Argo
5model feedback
Work breakdown
Worked at the intersection of computer vision, machine learning, MLOps, and data engineering.
Contributed to data and annotation services, ML dataset tooling, data lake access, workflow orchestration, migrations, APIs, and testing.
Helped connect research, labeling, data pipelines, training workflows, and production operations.
02
Data platform tooling
BRT devkit and related repos reference Athena data lake querying, DB connectors, data staging, image APIs, notebooks, and workflow utilities.
03
MLOps workflows
Kubeflow, Argo, EKS, Jenkins, Artifactory, and release processes show production platform work around ML teams.
Evidence notes
These are provenance cues for future polish. They keep the page specific without pretending every private archive is public proof.
- LinkedIn public snippets
- github.com/jclanoe-brt
- Local BRT repos and git history