IMC
Graduate Performance Engineer
About this role
IMC is hiring graduate performance engineers to apply quantitative research and advanced programming to optimize ultra-low-latency trading strategies. You'll work at the intersection of financial markets, systems engineering, and algorithmic development, collaborating with traders and engineers to gain competitive advantages in electronic trading.
What you'll do
- Conduct quantitative research on large datasets to analyze exchange technology and market microstructure
- Design and develop optimization strategies for liquidity taking and quoting in ultra-low-latency environments
- Build AI agents, ETL pipelines, and algorithms in Python to enhance trading performance
- Reverse-engineer and stress-test network and systems technologies to understand them deeply
- Collaborate with traders, hardware engineers, and software engineers to implement research findings
What they're looking for
- Proficiency in at least one programming language (Python preferred)
- Strong quantitative and analytical abilities
- Statistical modeling and machine learning experience
- Network technology and systems programming knowledge
- Problem-solving and reverse-engineering mindset
- Cross-functional communication and teamwork
- Understanding of financial markets and trading concepts
Benefits
- Discretionary bonus eligibility
- Comprehensive paid leave
- Insurance coverage
- Access to cutting-edge research environment
- Collaborative, high-performance culture
- Global career opportunities across multiple offices
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IMC
IMC builds trading technology and financial systems powered by software, machine learning, and hardware engineering. The company is hiring interns and graduate-level engineers and researchers across software, machine learning, and hardware disciplines to develop trading algorithms, research strategies, and collaborative technology solutions.
View all jobs at IMCLikely interview questions
- Walk us through a time you optimized a complex system—what metrics did you use to measure success?
- Describe your experience with large-scale data analysis and what programming languages you used.