Hi, I'm

Utkarsh
Singh.

Machine Learning & Data Engineer — I build intelligent systems.

A computer-science engineer who actually likes the unglamorous middle of the stack: data pipelines, ML systems and real-time processing. Currently at CommentSold in Bengaluru — writing clean code, learning in public, and keeping a running log of what I'm into.

01 — Profile

A pipelines person,
by practice.

§ 01 / 06
~/about

Computer Science Engineer by training, a pipelines person by practice. Currently a Machine Learning & Data Engineer at CommentSold, working on big-data tooling, ML pipelines and real-time processing.

Over the past few years I've deepened my expertise through hands-on projects and study — seeking not just knowledge but judgement. I believe in building meaningful products, not just features: every line of code can help or hurt a business, so I commit to clean, maintainable, scalable solutions and regular refactoring to keep technical debt honest.

Outside of code I'm a tech enthusiast with a keen interest in AI, ML and data science, and a fondness for thoughtful debate — well-chosen discussions spark growth and new perspectives.

Based inBengaluru, India
CurrentML & Data Eng · CommentSold
LanguagesEnglish · Hindi
FocusAI · ML · Data Science
Currently — a living log

What I'm on, right now.

live
~/now
Working

Real-time data at scale

Big-data tooling, ML pipelines and streaming at CommentSold.

CommentSold · 2025 →
Learning

MITx MicroMasters

Statistics & Data Science — depth over a rushed completion.

In progress · 2023 →
Exploring

LLMs, RAG & agents

Generative AI in production — retrieval, evals, guardrails.

Ongoing
Tinkering

Rust & systems

Picking up Rust for the fast, boring, reliable layer.

Side quest
02 — Experience

Work.

§ 02 / 06
~/work
2025NowBengaluru

ML & Data Engineer

CommentSold · ML pipelines & real-time data

Working with big-data technologies, ML pipelines, real-time data processing and building data pipelines at scale. Blending discipline with curiosity to ship clean, maintainable systems that earn their keep.

StackPython · Spark
ML pipelines
Real-time data
Big data
202125Bengaluru

Data Engineer

DataGrokr Analytics · pipelines & APIs

Built and scaled data pipelines and APIs for analytics workloads. Four years of hardening the unglamorous middle of the stack — the part that decides whether the graph stays flat or keeps paging people at 2 a.m.

StackPython · SQL
Data pipelines
API development
Cloud
03 — Education

Study.

§ 03 / 06
~/education
202324Online · MITx

MicroMasters · Statistics & Data Science

Massachusetts Institute of Technology

Actively working through the program — prioritising depth of understanding over a rushed completion. Goal is to master the concepts before sitting the final capstone exam.

FocusStatistics
Data science
202123Gurgaon

M.Sc. · ML, Data Science & AI

BML Munjal University

Deepened expertise across Machine Learning, Artificial Intelligence and Data Science — the theoretical grounding that makes the pipelines at work less mysterious.

FocusMachine learning
AI · data science
201721Phagwara

B.Tech · Computer Science (Hons.)

Lovely Professional University

Solid foundations in the core of computer science. Honours track, with a systems and algorithms focus.

FocusCS fundamentals
04 — Capabilities

Skills.

§ 04 / 06
~/skills
01

Software Dev.

// build & ship
  • Python
  • Go
  • TypeScript
  • Rust
  • Django / FastAPI
  • Postgres
  • Docker · k8s
02

Data Engineering

// move · model · store
  • Spark
  • dbt
  • Airflow
  • Kafka · Flink
  • Iceberg / Delta
  • Terraform
  • SQL (pg · presto)
03

Data Science

// measure & reason
  • Pandas · Polars
  • Applied stats
  • Experimentation
  • Visualization
  • NumPy / SciPy
  • Forecasting
  • Notebooks
04

AI & ML

// learn & serve
  • PyTorch
  • LLMs · Transformers
  • RAG · retrieval
  • scikit-learn
  • Vector DBs
  • MLOps · serving
  • Evals · guardrails
Let's talk

Building something intelligent?

I'm open to AI / ML roles, collaborations and the occasional advisory chat. Grab my résumé or send a note — I read everything.