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This internship focuses on researching low-latency ML inference and hardware acceleration, involving project ownership, collaboration with engineers, and presenting findings.

The Quantitative Developer will develop systems from research to production, build simulation infrastructure, manage feature pipelines, and troubleshoot issues in quantitative trading environments.

As a Software Engineer, you will build AI systems to enhance developer workflows, implementing agents and servers, and ensuring code reliability through evaluation pipelines.

Engineer and operate large-scale bare-metal Linux infrastructure, build automation and provisioning workflows, develop Python/Bash tools, extend monitoring/telemetry, manage configuration at fleet scale, troubleshoot performance and networking, and collaborate with stakeholders to maintain reliability and efficiency.

Design, build, and operate big-data and streaming platforms (Kafka, Hadoop, Dremio). Develop, deploy, and monitor data pipelines using Java, Python, Spark/Flink; collaborate on data modeling and ingestion, ensure data integrity and availability, act as a Big Data SME, and perform root-cause analysis.

Design and verify next-generation ASICs for latency-sensitive trading systems. Responsibilities include RTL development in SystemVerilog, verification and testing, debugging, integration, tooling and automation, and cross-team collaboration to meet performance and reliability goals.

Perform hands-on electronics lab work: validate and bring up circuit boards and ASICs, operate and maintain test equipment and fixtures, manage inventory and lab infrastructure, support manufacturing coordination, assembly, shipping, and documentation to enable hardware production and deployment.

Lead end-to-end IT audits globally to assess design and operating effectiveness of internal controls across technical platforms. Provide actionable recommendations, drive change, write clear reports, build relationships, and travel internationally (~25%).

Build, operate, and scale large-scale data storage platforms (Hadoop, S3-compatible, enterprise storage). Tune Linux for I/O performance, automate deployments with Ansible/Puppet, implement observability with Prometheus, and partner with engineers on storage- and Kafka-focused data solutions. Familiarity with Kubernetes and development in Java/Python required.

Serve as a strategic HR advisor to NYC business leads, driving talent strategy, performance coaching, engagement, data-driven insights, change initiatives, employee relations, and cross-HR collaboration to improve retention, development, and organizational effectiveness.