Duties: Develop new and enhance existing software and systems for complex, large-scale, and performant simulations serving quantitative models in algorithmic equity trading systems. Build and support reliable and scalable automated research workflows for internal quantitative researchers. Maintain and enhance the simulation infrastructure and integrations with other data sources and platforms. Conduct user research, gather user feedback, and engineer optimizations on various user workflows. Drive technical projects among internal and external stakeholders. Design and development new high performance components for the Rust-based trading and research platform. Participate in Rust related technical discussions. Provide mentorship to the company’s college new hires.

Minimum Requirements: Bachelor’s degree or equivalent in Computer Science, Computer Engineering, or related field. Position does not require specific years of experience but requires listed skills. Must have demonstrated knowledge of C++, Python, and Java. Must have demonstrated knowledge of data analysis tools such as Pandas, Jupyter or Notebooks. Must have demonstrated knowledge of Linux or other Unix operating systems. Must have demonstrated knowledge of databases and SQL. Must have demonstrated knowledge of developing applications utilizing IPC protocols, such as REST. Must have demonstrated knowledge of concurrency programming. Must have demonstrated knowledge in using common debugging programs such as GDB, or Valgrind. Must have demonstrated knowledge in working with kernel and/or OS-level computer architectures. Must pass company’s required skills assessment. Employer will accept any amount of academic coursework, or experience gained prior to the completion of a Bachelor's degree with the required skills.

Rate of pay: The base pay for this role will be between $165,000 and $325,000 per year. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.