Python Software Engineer
IMC · Not provided by source
MeritLog read this listing from IMC's Greenhouse job board and last checked it on September 9, 2026.
Source: the employer's Greenhouse job board. Open the original listing for current details.
Job details
- Work model
- Not provided by source
- Salary
- Not listed by source
- Location
- Sydney, Australia
Hiring context
How this role compares at IMC
IMC has 175 live roles in MeritLog’s catalog across 10 job families, and 53 of them are in engineering. 0 of those listings publish a pay range, a disclosure rate of 0%.
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Job description
At IMC, technology is not a department; it’s at the heart of everything we do. Developed in house, our innovative software makes millions of trading decisions daily, and we win by making better and faster decisions than our competition. IMC’s Sydney based Engineering teams work on a wide variety of applications, tools and functionalities, including trading algorithm implementations, option pricing, calculating volatility, simulation frameworks, market risk applications, trade reconciliation applications and data analysis & visualization tools for traders. We frequently need to develop not just the business applications themselves, but also the tools that keep our development process at the cutting edge. We are currently looking to expand our software engineering teams across our Strategy, Research tooling and Backbone teams. The Strategy Developers work alongside our Sydney-based options research and trading teams in designing and implementing systematic trading strategies. You will be responsible for engineering efforts in a Python-based ecosystem that empowers our researchers and traders to develop strategies from initial prototypes to production. In this role, you will also be involved in the tactical development of front-office trading, analysis, and visualization tools. The Backbone Developers create scalable business critical applications and tools to automate tasks supporting IMC’s Sydney Mid-Office and Risk Management departments. They gather requirements and feedback from a range of internal stakeholders in order to implement creative automation solutions via innovative coding practices. The Research Tooling Developers collaborates closely with APAC Quant Research and other engineering teams to build and enhance tools that drive cutting-edge quantitative research. Our systems empower researchers to run large-scale computations on distributed clusters, enabling the exploration of new trading strategies, model training, and back testing. Your Core Responsibilities: • Develop, test, deploy, and maintain high-performance Python applications. • Work closely with traders, researchers, quants, and fellow engineers to build scalable and reliable software solutions. • Take ownership of end-to-end development, from requirements gathering to production deployment. • Implement automation and optimization projects to enhance trading and research workflows. • Apply advanced automated testing practices and leverage daily deployments to achieve agile and incremental benefits. • Balance trade-offs between latency, throughput, simplicity, scalability, and maintainability in a complex technology landscape. Your Skills and Experience: • 5+ years of professional software engineering experience, with a strong focus on Python. • Experience working with numerical computing and data processing frameworks such as Pandas, NumPy, SciPy, Celery, Dask, or Spark. • Strong problem-solving skills and the ability to proactively tackle technical challenges. • Experience with automated testing and CI/CD pipelines. • Familiarity with Docker, Kubernetes, and Linux environments. • Exposure to distributed computing and modern cloud-based data processing technologies. • Strong communication skills and the ability to work with cross-functional teams including traders, researchers, and other engineers. • Prior knowledge of financial markets or trading is not required, but curiosity and a willingness to learn are essential. 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.
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