Quantitative Developer - Altas Technologies at IMC

At IMC, technology is at the core of everything we do. Our innovative in-house software drives millions of trading decisions daily, allowing us to outperform the competition through faster, more effective decision-making.

In 2023, IMC acquired Altas Technologies, a rapidly growing algorithmic trading firm with the ambition of creating tomorrow’s most technically advanced trading stack. By combining their highly advanced trading strategies with IMC’s execution and scaling capabilities, this move strengthens our position in the market and is an important step towards ensuring stability and long-term growth for the firm. 

Your Core Responsibilities:

You will become part of a core Quantitative Development team consisting of ~5 people working with cutting-edge technologies on both greenfield projects as well as optimizing existing systems and applications. The team has full end-to-end ownership of their stack. In this role you will:

• Build, optimize and deploy fully automated, low-latency, high-throughput trading systems to execute equity and cryptocurrency trades, including integrating real-time machine learning prediction systems.
• Design and maintain scalable data infrastructure for efficient ingestion, processing, and analysis of large datasets to support trading and research needs.
• Collaborate with researchers to translate advanced machine learning models and trading strategies into high-performance, production-grade implementations.
• Optimize market connectivity and exchange interactions to ensure low-latency, reliability, and execution efficiency in dynamic trading environments.*

 Your Skills and Experience:

• Highly experienced in Python combined with experience with either C++ and/or Rust.
• Experience with asynchronous/concurrent/multi-threaded and shared memory programming
• Experience with deployment tools and Bash/scripting abilities
• Hands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plus
• Experience with data processing pipelines, automated scheduling tools, and feature calculation engines is a strong plus
• Experience in architecting significant scale container-style Microservice Architectures from design and testing (CI/CD) to execution, and deployment. 
• Serious about clean code, simple but well-architected systems, and continuous improvement
• A track record of contributing to open-source projects in machine learning, data science, or distributed systems is a plus