Graduate Software Engineer - Digital Assets

IMC has a strong presence in traditional Finance and has been expanding into Crypto over the last years. Through its overseas affiliates, IMC provides liquidity and trades on many cryptocurrency exchanges and DeFi protocols. You can expect a dynamic, fast-paced environment that delivers a steady stream of challenges and opportunities, with one of the most exciting aspects of the job being our quick feedback loop in the research, development and deployment of strategies. As a Graduate Software Engineer, you‘ll be joining our core engineering team. You will contribute to our proprietary low-latency trading system, acquire market and trading data, implement ETL processes and collaborate with traders and researchers on improving the trading results. Your Core Responsibilities: Design, develop, maintain, and improve the in-house data infrastructure powering our market and trading data platforms, covering both batch and real-time streaming pipelines. Build and extend scalable data pipelines to support additional exchanges, trading venues, and new business domains. Work closely with software engineers, quantitative researchers, and traders to deliver reliable, high-performance data solutions for research and production trading. Contribute throughout the software development lifecycle, from design and implementation to testing, deployment, monitoring, and continuous improvement. Help improve the performance, reliability, scalability, and observability of our distributed data processing systems. Your Skills and Experience: Master or bachelor degree in Computer Science, Mathematics, Physics, or another related technical field. Strong programming skills in Python and at least one statically typed language, such as Java, Scala, Go, C++, or Rust. Experience with Python data analysis tools such as Jupyter Notebook, Pandas, NumPy, or modern distributed DataFrame frameworks through coursework, research, internships, or personal projects. Solid computer science fundamentals, including algorithms, data structures, concurrency and parallelism, networking fundamentals, software architecture, and writing clean, maintainable code. A performance-oriented mindset with an interest in building scalable distributed systems and understanding concepts such as latency, throughput, memory efficiency, serialization, backpressure, fault tolerance, and state management. Exposure to modern data engineering and data lake technologies such as Apache Spark, Apache Flink, Apache Iceberg, ClickHouse, Apache Kafka, Apache Airflow, Dagster, or similar technologies is a plus. Exposure to modern infrastructure technologies such as Kubernetes, Docker, CI/CD, GitOps, observability and monitoring is a plus. Excellent written and spoken English, with the ability to collaborate effectively in an international team. Passionate about designing, developing, testing, deploying, maintaining, and continuously improving software. Location and Office Culture: IMC office in Zug, Switzerland. Note that this is an onsite role, with some but limited flexibility for working from home. You can expect a dynamic, fast-paced environment that delivers a steady stream of challenges and opportunities. One of the most exciting aspects of the job is our quick feedback loop in the research, development and deployment of strategies. We give people lots of responsibility and the support they need to make an impact from day one. We promise you a flat structure and an open, collaborative culture that stimulates the sharing of ideas, knowledge and technology between our teams and offices. About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.