Performance Engineer: Latency & Systems for Trading

Supergrads; Amsterdam; On-site; EUR 70,000 - 110,000; Full time

Job summary

Supergrads in Amsterdam seeks a technically curious Performance Engineer to understand and improve the performance of complex electronic trading environments.

You will investigate how trading and exchange infrastructure behaves in real-world conditions, identify latency sources, and develop measurable improvements using data and experimentation. This role lies at the intersection of systems engineering, quantitative analysis, networking and experimental research.

Qualifications

• Advanced professional experience with Python and Networks or Linux is a must-have.
• Strong knowledge of computer architecture, networking and/or Linux with expertise in at least two areas.
• Analytical mindset with experience using data/experimentation to answer difficult technical questions.

Responsibilities

• Investigating complex systems: use black-box analysis and experiments to understand performance and where improvements can be made.
• Data-driven research: work with large data sets to uncover patterns and behavior in exchange/network tech.
• Performance optimization: identify latency and efficiency improvements across the stack from connectivity to trading infrastructure.
• Building and testing ideas: develop prototypes and proofs-of-concept before moving to implementation.
• Working across disciplines: collaborate with traders, engineers, hardware and infrastructure teams to translate findings into practical changes.
• Analyzing network behavior: study large network data to validate theories and explain real-world system behavior.
• Independent problem solving: own investigations from question to analysis and recommendations.

Skills

Python

Networking

Linux

Job description

Supergrads in Amsterdam seeks a technically curious Performance Engineer to understand and improve the performance of complex electronic trading environments.

You will investigate how trading and exchange infrastructure behaves in real-world conditions, identify latency sources, and develop measurable improvements using data and experimentation. This role lies at the intersection of systems engineering, quantitative analysis, networking and experimental research.