chandramullu

Quantitative Developer | Python

I am a Python quantitative developer based in Bangalore with 5+ years of experience building production systems for financial risk and real-time analytics. My work spans distributed computing, event-driven data pipelines, backend services, and performance optimization.

At Millennium (July 2022 - February 2026), I helped build the Enterprise Risk Technology platform, including distributed stress calculations across 2M+ positions and 4,000 scenarios, Python/Java risk libraries using Apache Arrow, and on-demand Ray/Dask compute. I built a data orchestration library adopted by 100+ developers, reduced risk-reporting SLAs by 3 hours, and delivered 50% faster deployments.

Previously, as an AI Backend Engineer at Marsview.ai, acquired by Eltropy (August 2021 - June 2022), I developed production NLP microservices for real-time text, audio, and video analytics, serving up to 1 million requests. Redis caching improved asynchronous stack performance by 900%.

My core tools include Python, SQL, Ray, Dask, Apache Arrow, Airflow, PostgreSQL, DuckDB, Redis, Pandas, Polars, NumPy, AWS, Docker, Kubernetes, GraphQL, and CI/CD. I also work with NLP, MLOps, LlamaIndex, and MCP/LLMs.

Projects include Igloo, a distributed SQL query engine using ADBC, DataFusion, Apache Arrow, Apache Iceberg, and CDC (https://igloodb.github.io/), and Portfolio Pulse, a Streamlit portfolio analytics app with real-time prices and risk analysis (https://portfolio-pulse.streamlit.app/).

I hold an Integrated B.Tech in Computer Science from IIIT Nuzvid (2018 - 2022), with an 8.73 CGPA. I am interested in Python quantitative development, backend engineering, distributed systems, and data/AI infrastructure roles.

Experience: 5 years

Yearly salary: $150,000

Hourly rate: $100

Nationality: 🇮🇳 India

Residency: 🇮🇳 India

Experience

Quantitative Developer

Millennium

2022 - 2026

July 2022 - February 2026 • Early member of the Enterprise Risk Technology team; owned foundational systems from design and implementation through production. • Designed and built distributed firm stress calculations across 2M+ positions and 4,000 scenarios. • Built an enterprise risk calculation library with Python and Java bindings using Apache Arrow. • Implemented event-driven streaming ETL for CIO-office risk reporting, reducing SLAs by 3 hours. • Designed a data orchestration library adopted by 100+ developers. • Built compute-grid to provision Ray/Dask clusters on demand with resource quotas and cost-aware autoscaling. • Built Plotly Dash risk interfaces with standard and user-triggered ad hoc views. • Established a cloud-native deployment pipeline, achieving 50% faster deployments. • Created GraphQL queries for risk calculations at entity and fund-of-funds levels.

AI Backend Engineer

Marsview.ai (acquired by Eltropy)

2021 - 2022

August 2021 - June 2022 • Developed and deployed production NLP microservices for real-time text, audio, and video analytics, serving up to 1 million requests. • Integrated real-time APIs with Eltropy One to support secure, compliant financial-institution messaging. • Built a Redis LRU cache for token embeddings, improving asynchronous stack performance by 900%.

Skills

aws

backend

ci-cd

docker

git

graphql

kubernetes

linux

nlp

quantitative

redis

sql

python

english

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