Jobs at Two Sigma

Provides middle-office operational support for trading desks, including trade-break resolution, reconciliations, corporate actions, locates, buy-ins, risk controls, and operational data integrity. Coordinates cross-functional projects, supports new strategies, and improves tools, workflows, dashboards, and controls. Requires broad understanding of the trade lifecycle across equities, futures, and options, strong analytical and communication skills, and experience with Excel and Bloomberg.

Build and scale production-grade AI/ML systems for quantitative research. Responsibilities include translating research prototypes into maintainable software, optimizing GPU training and inference pipelines, designing data-loading and batching infrastructure, extending research libraries for agentic workflows, and improving codebase quality, testing, and scalability. The role partners closely with machine learning researchers and requires strong Python engineering, GPU systems experience, and familiarity with modern ML frameworks and agent technologies.

Designs and maintains scalable distributed infrastructure across on-premise and public cloud environments. Evaluates emerging technologies and open-source tools, supports incident response and on-call operations, establishes platform engineering standards, and leads cross-functional initiatives from requirements through adoption. The role enables engineering and data science teams to operate research, simulation, and trading workloads efficiently and reliably.

Develop systematic quantitative signals and alpha models focused on ETF and index trading inefficiencies. Gather, manage, and analyze financial and economic data, including market microstructure datasets, and support portfolio construction and strategy implementation. Collaborate with researchers, portfolio managers, engineers, and trading teams to implement new strategies. The role also involves managing research projects end to end and mentoring junior researchers.

Lead enterprise operational risk control assurance testing across the firm. Build testing frameworks, document processes and controls, evaluate effectiveness, identify gaps and failures, manage remediation tracking, develop risk dashboards, and produce enterprise and corporate risk reporting. Collaborate with risk leads, technical and business stakeholders, and senior leadership while managing projects, schedules, meetings, and consensus-building.

Architects and develops secure authentication, authorization, and identity management infrastructure. Builds software in Python or Go, modernizes legacy systems into cloud-native platforms, improves observability and documentation, evaluates security technologies, makes architectural decisions, leads cross-team initiatives, and mentors engineers while maintaining high security and reliability standards.

Lead engineering and operational support for critical production systems. Develop automation, services, tools, and libraries; improve observability, scalability, availability, and operability; monitor production environments; enforce change management and automated testing; collaborate with software engineering teams on architecture and reliability; and participate in on-call support.

Build and deepen relationships with private banks, wealth managers, family offices, and ultra-high-net-worth investors. Source opportunities, position investment products, guide clients through diligence and onboarding, and provide high-touch ongoing engagement. The role also involves client profiling, presenting complex investment concepts, managing follow-up, optimizing the client platform, and complying with regulatory procedures. Frequent interaction with clients and prospects across the United States is required.

Develop and scale quantitative software, models, systems, tools, frameworks, and libraries supporting machine learning, quantitative research, and trading. Collaborate with research partners to prototype and implement models, design quantitative architectures, optimize performance, and improve scalability. The role requires algorithm development, scientific computing, and expertise with Python-based numerical and machine learning technologies.

Develop and manage AI fluency programs that help employees adopt agentic AI across business functions. Responsibilities include designing curricula, delivering training and workshops, measuring learning outcomes, developing stakeholder adoption strategies, assessing knowledge repositories, and creating systems to capture and organize institutional expertise. The role requires translating complex technical concepts for varied audiences and executing autonomously in an ambiguous, greenfield environment.

Conduct fundamental credit analysis of convertible issuers, evaluating capital structures, liquidity, covenants, recovery, and refinancing risk. Assess stressed credit positions and support portfolio sizing, hedging, and exits. Analyze primary market transactions, monitor portfolio exposures, develop issuer views, and identify emerging risks. Build scalable, data-driven credit analysis tools using AI, LLMs, and agentic workflows while presenting concise recommendations to portfolio managers.

Lead research and production development for LLM post-training in quantitative finance. Responsibilities include designing RLHF, DPO, reward modeling, and policy optimization methods; building preference-data and training infrastructure; managing large-scale compute; developing evaluation frameworks; collaborating with quantitative researchers; and supporting production systems.

Research and develop execution models, trading tactics, market impact models, simulators, scheduling methods, and short-horizon signals. Analyze order book, quote, trade, order, and fill data to improve execution costs and capacity. Design production experiments, evaluate execution metrics, and deploy research into trading systems while collaborating with portfolio management, modeling, engineering, and trading teams.

Manage investor relations and client services for current and prospective investors. Responsibilities include handling fund inquiries, producing investor materials, overseeing subscriptions, redemptions and transfers, maintaining CRM and client portal capabilities, improving data integrity, and leading technology-driven service initiatives. The role collaborates with internal teams and fund administrators, establishes operational governance and quality standards, and may lead or mentor associates.

Conduct AI and machine learning research during a 10-week summer internship. Develop techniques and infrastructure, write code, run experiments, analyze noisy financial data, and collaborate with experienced researchers. The role focuses on deep learning, large language models, reinforcement learning, data pipelines, cloud computing, and multi-machine research environments.

Conduct quantitative research for macro and fixed-income markets by developing alpha-generating investment models. Responsibilities include idea generation, feature development, alpha forecasting, monetization, portfolio construction, portfolio management, dataset analysis, and applying artificial intelligence and machine learning techniques. The role involves collaborating with quantitative researchers and developers to solve complex investment problems and communicate findings clearly.

Monitor systematic trading strategies, identify portfolio and investor risks, and escalate issues to trading, portfolio management, engineering, and modeling teams. Develop automated alerts, reporting, and quantitative analysis tools; investigate root causes; analyze strategy behavior and risk; document and improve operational risk processes; and collaborate on initiatives across diverse partner teams.

Conduct AI and machine learning research for financial-market applications, developing predictive models, infrastructure, prototypes, and production systems. Apply deep learning, large language models, and reinforcement learning to noisy data. Write code, run experiments on cloud and CPU/GPU infrastructure, collaborate across teams, contribute to products, and engage with internal and external research communities through publications and conferences.

Develop and optimize low-latency quantitative software for research, feature construction, alpha generation, and trading. Partner with quantitative researchers to prototype and implement components in Rust, C++, and Python, analyze real-time and simulated trading data, and research improvements to models, feature pipelines, and strategies. Build deep expertise in research systems, quantitative domains, and financial markets while delivering high-quality, high-performance software.

Own full-cycle recruiting for corporate functions, including sourcing, candidate assessment, interviews, offers, closing strategies, and hiring metrics. Build consultative partnerships with HR Business Partners and hiring managers, represent the company externally, manage search-firm relationships, and support cross-functional recruiting projects. The role requires strong organization, communication, collaboration, and independent problem-solving skills, with a focus on attracting diverse, high-quality talent.