Senior Full Stack Data Platform Engineer

About the role

Senior Full Stack Data Platform Engineer

Founded in 1989, Millennium is a global alternative investment management firm. Millennium seeks to pursue a diverse array of investment strategies across industry sectors, asset classes and geographies. The firm’s primary investment areas are Fundamental Equity, Equity Arbitrage, Fixed Income, Commodities and Quantitative Strategies. We solve hard and interesting problems at the intersection of computer science, finance, and mathematics. We are focused on innovating and rapidly applying innovations to real world scenarios. This enables engineers to work on interesting problems, learn quickly and have deep impact to the firm and the business.

At Millennium, we are redefining how investment decisions are made. We don't just look at balance sheets; we harness the chaos of the real world. By analyzing vast amounts of unstructured data—from news briefings and earnings call audio to regulatory documents—we provide our Portfolio Managers (PMs) with the "informational edge" (Alpha) they need to outperform the market.

The Role

We are seeking a Senior Full Stack Software Engineer with deep expertise in building high-throughput data platforms.

In this role, you will architect scalable data platforms using Python, Java, C++, build robust APIs, and enable processing of data using genAI techniques. You will build and optimize a config-driven, plugin-enabled data platform that will allow the construction of DAGs for data processing. You will then apply the platform to build reusable components and pipelines that will ingest gigabytes of unstructured text, audio, and video. You will enable a variety of rich data consumption use-cases by building the right abstractions and APIs for data consumers.

You will be the bridge between complex ML research and real-time trading decisions, working in a poly-language environment (Python, Java, C++) where performance is paramount.

Key Responsibilities

- High-Performance Data Pipelines: Architect low-latency, high-throughput platform that enables rapid development of pipelines to ingest and normalize unstructured data (PDFs, news feeds, audio streams).

- AI & ML Integration: Build the infrastructure that wraps and serves NLP and ML models. You will ensure that model inference happens in real-time within the data stream.

- Backend Microservices: Develop robust backend services to handle metadata management, search, and retrieval of processed alternative data.

- System Optimization: Tune the platform for speed. In financial markets, milliseconds matter; you will optimize database queries, serialization, and network calls to ensure data reaches the PMs instantly.

- Data Strategy: Implement storage strategies for unstructured data, utilizing Vector Databases for semantic search and Distributed File Systems for raw storage.

Required Qualifications

- Data Platform Experience: Minimum 5+ years of software engineering experience, preferably building data platforms.