Top Tech Jobs & Startup Jobs

Develop and optimize large-scale machine learning infrastructure, collaborating with quantitative researchers, and enhancing platform capabilities for scalability and efficiency.

Build and scale Tower's ML research platform: design distributed training pipelines, enable large-scale experimentation across HPC and cloud, improve experiment management, model/version tracking, data pipelines, observability, and compute/resource efficiency while partnering with researchers.

Design, operate, and improve large-scale HPC compute and storage across on-prem and cloud. Maintain Linux systems, troubleshoot OS/storage/network/cluster layers, manage batch/container workloads, build management tools and observability pipelines, automate workflows, and optimize cluster utilization and performance.

As a Quant Developer, you will enhance the research framework and support quantitative research teams, optimizing trading tools and systems.

As a Quant Developer, improve research frameworks, develop tools for trading strategies, and support the quantitative research team on-site.

Lead and architect a low-latency, high-frequency cryptocurrency trading platform. Manage and mentor a distributed global engineering team, collaborate with traders and stakeholders, optimize network and systems performance, and build historical data and simulation systems to support trading strategies.

Maintain and support order management and market data systems for electronic exchanges. Provide L1/L2 production support, monitor system health, coordinate with trading, risk, and compliance teams, architect reliability improvements, act as broker/exchange technical contact, and provide periodic after-hours coverage.

Provide monitoring, troubleshooting, and support for production, office, and data center networks. Assist with network changes, market connectivity testing, circuit migrations, and collaborate with vendors and internal teams. Participate in on-call rotation for global network operations.

Develop and improve the research framework and tools for a quantitative trading team. Provide day-to-day on-site support to quantitative researchers, implement production-grade Python and C++ code, and integrate statistical libraries and workflow/task scheduling solutions. Collaborate with traders and engineers to enhance research infrastructure and execution capabilities.

Design, implement, and optimize high-performance, low-latency trading infrastructure for research and production. Partner with researchers and traders to build market data, execution, backtesting, and deployment systems. Develop tools for prototyping, simulation, monitoring, risk management, and performance analysis across the strategy lifecycle.