Yuyang Wang

Yuyang Wang

Software Engineer
Santa Clara, California

I build production LLM agent and inference platforms and the data systems underneath them.

At Polaris Wireless I shipped an AI data analysis platform end to end with self-hosted vLLM serving and a 133-case evaluation harness, took billion-record analysis from two minutes to under thirty seconds, and own production monitoring for customer deployments in two countries.

Now

  • Leading the AI data analysis platform at Polaris Wireless and operating its self-hosted vLLM inference.
  • OmniScanner just shipped on the App Store; HikeGPS is next in line for an update.
  • Writing deep dives on ClickHouse co-presence detection and natural-language workflow agents.

Updated September 2026

Experience

More about me

Software Engineer · Polaris Wireless

Jun 2024 — Present

Full-time · Santa Clara, CA

  • Shipped an AI data analysis platform end to end in Python (FastAPI, LangGraph, PostgreSQL, React): a streaming agent runtime with disconnection-safe resumable runs, checkpointed state, MCP tools, JWT/RBAC access controls, human-in-the-loop approval, reusable agent skills, and an nsjail sandbox for model-generated code. Agents run governed text-to-SQL across five database engines (ClickHouse, DuckDB, SQL Server, MySQL, PostgreSQL).
  • Deploy and operate the platform’s self-hosted vLLM inference on GPU: own model deployment and upgrades, tune KV-cache memory, batching, and context length for throughput and latency, and debug the serving path in production.
  • Built a 133-case end-to-end evaluation and regression harness that grades each agent answer in four layers — tool routing, arguments, results, and rendered charts and maps — against a ClickHouse ground-truth oracle. It drove accuracy to 97% and cut suite runtime 57% by fixing the tool-call and grounding defects it exposed.
  • Cut co-presence analysis, which scores which subscribers met a target, from two minutes to under 30 seconds across billions of mobility records by redesigning the ClickHouse pipeline, and derived and documented its statistical confidence model.
  • Built and own production KPI monitoring for customer deployments in two countries using Flask, Grafana, Prometheus, Loki, and Docker: 100+ KPIs across 48 dashboards, 15 alert rules, scheduled 15-minute analysis jobs, a web command portal, and automated monthly reports.
  • Developed natural-language workflow agents for the AIGIS product: intent classification, fuzzy resolution of target and geofence names, natural-language date parsing, parameter validation, and generation of structured API requests.
  • Technical lead for the analysis platform: set its architecture and drove delivery with an offshore engineering team. Mentored several interns and conducted technical interviews for 10+ engineering candidates across multiple teams.

Selected projects

All projects

An open-source TeslaMate client for iPhone with live telemetry, trip history, and battery analysis.

  • iOS
  • Open source
  • Data

Offline trail maps for iPhone, with on-device species identification, hazard warnings, and GPS recording.

  • iOS
  • Maps
  • On-device ML

CYD World Clock

2025 — present

An ESP32 desk clock with four time zones, market hours, weather, holidays, and touch controls.

  • Hardware
  • Open source

Writing

All posts
1 min readStarting to write things downNotes on AI agents, data infrastructure, and small hardware projects.7 min readLessons from operating a small Hadoop data clusterPractical failure modes and fixes across HDFS, YARN, Spark, ZooKeeper, HBase, and ClickHouse.2 min readTurning Ericsson Cell Trace files into analysis-ready CSVA dependency-free Python decoder for the stable framing and common headers inside Ericsson Cell Trace files.3 min readIMEI, IMSI, MSISDN, and TAC: cellular identifiers without the confusionA practical guide to the identifiers for devices, subscriptions, phone numbers, and device models.