Quant jobs / Two Sigma

Quantitative Software Engineer – Generative AI

A machine learning engineering role in a news engineering team that turns unstructured text such as news, social media and filings into usable data. It builds NLP and LLM services, data pipelines and signal-mining tools.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Build and maintain NLP and LLM services for research and production
Prototype generative AI methods with modelling partners
Run data pipelines delivering large event volumes to production
Support automatic signal mining over a large text corpus

What they ask for

Required

BS in CS, machine learning or similar
Minimum 1 year; 3–10 years preferred deploying ML
NLP and LLM experience
PyTorch or TensorFlow
Translating research papers into practical systems
Comfort in fast-paced, cross-functional teams

Preferred

Advanced degree
Machine learning publications

Education: BS in computer science, machine learning or a related technical field; advanced degrees and ML publications highly desired.
Experience: Minimum 1 year; 3–10 years preferred deploying machine learning
Languages and tools: Python
PyTorch
TensorFlow

How to prepare

Build an NLP pipeline on financial news or filings with embeddings or an LLM
Fine-tune and evaluate a transformer model with PyTorch
Learn to test text-derived signals for leakage and timing
Build a scalable text-processing pipeline

What to study

The NLP and ML Quant Researcher roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on Two Sigma’s site before applying: requirements, location and pay can change after we check them.

View the posting on Two Sigma’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Two Sigma and doesn’t handle applications.