Top Tech Jobs & Startup Jobs in NYC, NY

Lead development of complex data pipelines, AI/ML systems, and software solutions. Provide technical leadership, mentor engineers, conduct code reviews, make architectural decisions, and collaborate with technical and non-technical stakeholders. Maintain hands-on Python development using scalable data engineering practices, cloud platforms, containerization, CI/CD, and machine learning frameworks. Experience with large language models and AI agents is highly desirable.

Conduct ML research to produce predictive trading signals, design deep learning architectures, apply LLM-based agentic methods, implement signal compression and combination, build model frameworks for investment use, and collaborate with portfolio managers and researchers.

The role involves writing low latency C++ code, implementing trading infrastructure, and adapting systems for the next generation trading platform, requiring collaboration with portfolio managers.

Support Portfolio Managers with alpha research, modeling, and implementation of quantitative trading strategies while building tools for quantitative research.

Develop systematic strategies to exploit market inefficiencies, manage a quantitative investment portfolio, and build a research pipeline.

Develop and manage systematic strategies for a diverse range of asset classes, utilizing quantitative management techniques to drive investment portfolios.

Lead a high-performing team to manage electronic execution, focusing on recruitment, development, and collaboration while adapting best engineering practices.

WorldQuant seeks candidates for its Technology team to join a community for potential future opportunities. The role highlights collaboration and innovative thinking.

Design, implement, test and deploy high-performance, large-scale software systems to support quantitative research and production portfolios. Own Linux/C++ codebases, apply system programming, concurrency, and data structures expertise, and collaborate with researchers to build scalable distributed and streaming data platforms.

Monitor automated execution across equities, FX, futures and other asset classes; provide first-line support for execution flow; analyze large datasets to improve automation and reduce implementation costs; run projects to add liquidity and lower execution costs; interface with portfolio managers, brokers, risk, compliance and senior management.