Quantitative Developer — Research Systems — San Jose

This San Jose, CA-based, fully remote Quantitative Developer — Research Systems position will build the research platform used to create reproducible market studies at scale. Applicants must live in the local area, which gives the team Pacific Time review of data-intensive workflows, the U.S. close, and overnight processing.

Compensation and Benefits

About the Role

In this San Jose, CA role, you will be accountable for research infrastructure, point-in-time data integrity, experiment lineage, and reliable numerical workloads while supporting Pacific Time review of data-intensive workflows, the U.S. close, and overnight processing. The work requires direct communication, explicit limits, and records that remain useful after market conditions change.

San Jose Operating Focus

The San Jose opening emphasizes scalable research systems, measurable latency, and careful release validation. Large datasets and time-sensitive systems need separate measures for correctness, latency, and cost. The opening reviews the U.S. close while also preparing overnight workflows that must be ready before the next session. Production improvements are accepted only when tests show that speed did not weaken point-in-time integrity or auditability. For this role, that means direct ownership of research-platform reliability, experiment lineage, and large time-series workloads during Pacific Time review of data-intensive workflows, the U.S. close, and overnight processing.

First Review Cycle

The initial San Jose, CA review combines Pacific Time review of data-intensive workflows, the U.S. close, and overnight processing with a controlled examination of research-platform reliability, experiment lineage, and large time-series workloads. Each material observation needs a source, a time, and a defined owner. One required check is: Improve experiment tracking, lineage, and reproducibility. The next required check is: Optimize large time-series workloads. The San Jose opening emphasizes scalable research systems, measurable latency, and careful release validation. You will identify any assumption that remains untested after both checks. The cycle ends with a short decision record, its limit, the next check, and each unresolved question. Another specialist must be able to trace the work through research infrastructure, point-in-time data integrity, experiment lineage, and reliable numerical workloads.

Responsibilities

• Develop reusable data and backtest infrastructure
• Improve experiment tracking, lineage, and reproducibility
• Optimize large time-series workloads
• Add tests that detect leakage and inconsistent data vintages
• Own research-platform reliability, experiment lineage, and large time-series workloads during Pacific Time review of data-intensive workflows, the U.S. close, and overnight processing.

Required Qualifications

• Production Python and SQL experience
• Strong knowledge of distributed data systems and numerical workloads
• Experience supporting quantitative researchers

Preferred Qualifications

• Experience with workflow orchestration, columnar data, and cloud research environments
• A record of improving speed without weakening correctness or auditability
• Experience collaborating across time zones while maintaining the operating coverage assigned to the San Jose, CA opening.

Benefits

• Medical, dental, and vision plan options with substantial company support
• 401(k) plan with company matching
• Flexible paid time off and company holidays
• Paid parental and caregiver leave
• Annual learning, conference, and professional-development budget
• Remote-work equipment and home-office support
• Performance-bonus and equity eligibility based on role and level

Benefits are subject to plan terms and eligibility requirements.

How to Apply

Submit a current resume through the application form for the San Jose, CA opening. A short cover letter is optional. We will contact qualified applicants about the interview process and next steps.

Equal Opportunity

Anemoi provides equal employment opportunities without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or any other status protected by applicable law.