Software Engineer, Trumid

• Minimum of 4+ years of professional experience in software engineering, with a focus on Python in a data-intensive or system development setting
• Strong proficiency in Python and at least one compiled programming language (e.g., C++, Java)
• Proven ability to design and implement scalable solutions that integrate well into distributed systems
• Solid grasp of algorithms, data structures, and software design principles
• Experience with Docker, relational and NoSQL databases, as well as data processing techniques (e.g., ETL, stream processing)
• Good knowledge of Git and CI/CD best practices

Desirable

• Joining Trumid as a software engineer means being part of a small, highly productive, and efficient team
• As a Python Software Engineer on our Data and AI team, you’ll work alongside world-class engineers, data scientists, and quants to build the core analytics infrastructure that drives our trading platform
• From deploying machine learning models to optimizing real-time systems, your contributions will directly impact the efficiency and scalability of our operations
• This is an opportunity to work in a fast-paced, cutting-edge environment and be a key player in shaping the future of our platform
• Be recognized as top developer talent, driving exceptional results and continuously pushing the boundaries of what’s possible in the Python ecosystem
• Architect, develop, and maintain robust, scalable software that powers Trumid's analytics and trading operations, handling millions of data points in real-time
• Collaborate closely with machine learning engineers, quantitative researchers, and cross-functional teams to build systems that optimize performance for real-time trading and analytics
• Lead the entire software development lifecycle, from concept and design to testing and deployment, ensuring maximum speed, scalability, and security of applications
• Integrate advanced models and algorithms into production, with a focus on reliability, efficiency, and real-world applicability
• Mentor and support junior engineers, fostering a collaborative and high-performance engineering culture
• Solve complex problems and enhance our trading infrastructure to support high-performance, low-latency trading systems
• Develop and optimize data pipelines and distributed computing environments to handle large-scale financial data
• Ensure the seamless integration of machine learning models into production environments, collaborating with the Data Science and Quant teams to streamline workflows
• Maintain a focus on continuous improvement, regularly enhancing the performance and functionality of our systems