Yiping Deng

Tech Lead II · AI Data · HubSpot

Making AI work.
At scale.

I build the data platforms behind AI at HubSpot — from distributed systems and vector search to GPU infrastructure and observability.

Explore my work Download CV

✳Based in Dublin, Ireland.
Building for the bigger picture.

A builder’s perspectiveFig. 01

Behind every intelligent app,
there’s a good system.

Data. Infrastructure. Intelligence.

Selected impact

7B+production ANN vectorsRAG & semantic search

80%less Spark support loadAI-agent job auto-tuning

2 TBingested every dayAI inference & feedback

$90K → $5Kmonthly storage costHBase migration

01 / What I build

The foundations
behind the possibilities.

Reliable platforms. Thoughtful abstractions.
Room for the next big idea.

Data platforms

Modernizing Spark infrastructure, helping build Apache Iceberg infrastructure, and making a $6–7M/year Spark fleet’s costs visible.

Apache Spark
Apache Iceberg
Data lineage

AI infrastructure

Scaling vector search to 7B+ production ANN vectors across 200+ indices, and building inference and feedback pipelines that ingest 2 TB/day.

Vector search
RAG
GPU infrastructure

Observable systems

Building OpenTelemetry tracing and storage for all AI agents at HubSpot, and using AI agents to analyze data-entity lineage graphs.

OpenTelemetry
AI observability
LLMOps

Selected projects / GitHub

Built out of curiosity.

All repositories

A few things I’ve built outside the day job — from GPU experiments and developer tools to useful little systems for everyday life.

GPU learning lab

Learning CUDA

A hands-on GPU programming notebook: CUDA matrix-multiplication kernels, Triton exercises, and custom PyTorch extensions.

CUDA
Triton
PyTorch

View on GitHub

Agent tooling

Codex Tool Mock

Mock shell-tool responses and verify expected commands with reusable fixtures, exact or regex matching, and pytest helpers.

Python
Testing
Agent evaluation

View on GitHub

Data tooling

parquet-cat

A Rust CLI for exploring Parquet files on S3, including folders, SQL queries through DataFusion, and AWS profile support.

Rust
Apache Parquet
DataFusion

View on GitHub

Developer experience

Codebase Prompt Generator

Turn a Git repository into structured AI context, with a file tree, source contents, include/exclude patterns, and .gitignore support.

Python
CLI
AI context

View on GitHub

Hardware experiment

Kindle LLM Usage

An e-ink dashboard for LLM usage and local coding-agent activity, with touch navigation, cached views, and explicit stale-data states.

Python
Lua
E-ink

View on GitHub

Everyday automation

CatLink CLI

A Python CLI for CatLink smart litter boxes: device status, logs, cleaning controls, and authentication backed by the system keyring.

Python
IoT
CLI

View on GitHub

02 / The journey

Built over time.

The full CV

Jun 2024 — PresentCurrent

HubSpot / Dublin, Ireland

Tech Lead II · AI Data

Own and modernize Spark infrastructure; introduced AI-agent job auto-tuning, cutting Spark support load by 80%.
Built cost tracking for a $6–7M/year Spark fleet and helped build HubSpot’s Apache Iceberg infrastructure.
Built an OpenTelemetry tracing and storage system covering all AI agents at HubSpot; use AI agents to analyze data-entity lineage graphs.
Scaled vector infrastructure for RAG and semantic search to 7B+ production ANN vectors; current infrastructure supports 200+ indices.
Built AI inference/feedback pipelines ingesting 2 TB/day; introduced JupyterHub and NVIDIA DGX H100 infrastructure.
Grew the team to six people and helped establish two spin-out teams focused on JupyterHub and vector databases.

Mar 2023 — Jun 2024

HubSpot / Dublin, Ireland

Tech Lead I · AI Data and MLOps

Maintained a feature store aggregating internal APIs for AI model serving; implemented compliance workflows and scaled AI data collection across multiple data centres.

Jan 2022 — Mar 2023

HubSpot / Dublin, Ireland

Senior Software Engineer I · AI Infrastructure

Cut monthly AI inference and feedback storage costs from $90K to $5K by migrating away from HBase.

Oct 2020 — Jan 2022

HubSpot / Dublin, Ireland

Software Engineer · AI Infrastructure

Maintained Kubernetes GPU infrastructure serving 1B+ AI inferences/day and large-scale HBase storage for inference and feedback data.
Standardized automated training pipelines for 6+ ML models, retrained weekly using user feedback.

Earlier experience 2018–2020

Sep 2019 — Aug 2020

HubSpot / Dublin, Ireland

Software Engineer Intern · AI Infrastructure

Implemented automated metrics and performance-tracking pipelines for ML models in the AI Infrastructure team.

Jun 2019 — Aug 2019

Amazon / Luxembourg

Software Development Engineer Intern

Built an internal UI for technical program managers to review machine-translated product catalogue content.

Feb 2019 — May 2019

Jacobs University Bremen / Bremen, Germany

Research Assistant · Marine and Robotics Systems

Researched autonomous-driving algorithms using ROS, OpenCV and PyTorch.

Jun 2018 — May 2019

Ubimax / Bremen, Germany

Software Engineer · Working Student

Built a SqueezeNet training microservice for automotive use cases; deployed models to Google Glass Enterprise and Vuzix M300 with TensorFlow Lite.

03 / A little about me

Curiosity is
the common thread.

My work sits where data infrastructure meets machine learning: the systems that collect, store, retrieve, and make sense of data at scale. At HubSpot, I’ve grown from an AI infrastructure engineer into a tech lead, building platforms and teams along the way.

I’m also a contributor to open-source infrastructure and a co-author of research in formal theorem proving. From mathematical foundations to production systems, I like understanding how things work — and making them work better.

Find me on GitHub

Education / 2017–2020

BSc Computer Science

Minor in Intelligent Systems

Jacobs University Bremen

Coursework in machine learning, algorithms, data structures, operating systems, and computer vision. Research in formal logic and marine robotics.

Languages & ML

Python
Java
C++
Rust
Scala
CUDA
Triton
PyTorch
TensorFlow Lite

Data & infrastructure

Apache Spark
Apache Iceberg
Kubernetes
AWS
Snowflake
HBase
Qdrant
OpenTelemetry
JupyterHub

Areas

MLOps
LLMOps
RAG
Vector search
GPU programming
AI observability
Data pipelines
Data lineage

04 / Beyond the day job

Shared with the community.

Open source

Qdrant

Four merged contributions to the open-source vector database: peer mTLS, HTTPS client-certificate validation, live TLS certificate rotation, and clustered-collection regression tests.

Explore the contributions

Research / May 2018