Quantitative Trader — Multi-Asset — San Francisco

Anemoi Predictive Technology LLC.; San Francisco (CA); Remote; USD 190,000 - 285,000; Full time

Benefits offered by this job

Performance bonus

Equity eligibility

Job summary

Anemoi Predictive Technology LLC in San Francisco, CA is seeking a fully remote Quantitative Trader — Multi-Asset to trade and evaluate systematic strategies across liquid equities, ETFs, futures, and FX. Applicants must live in the local area to align with Pacific Time coverage of late-session behavior and research handoffs.

The role emphasizes live cross-asset exposure, instrument-specific mechanics, funding, rolls, execution, and incident controls.

Qualifications

• 4+ years of experience in quantitative trading.
• Live cross-asset exposure and risk management experience.
• Strong background in incident response and production controls.

Responsibilities

• Manage live exposures and instrument-specific risk limits.
• Review execution quality, funding, rolls, and calendar effects.
• Research cross-asset relationships without forcing unstable correlations.
• Lead incident review and operating-control improvements.

Job description

This San Francisco, CA-based, fully remote Quantitative Trader — Multi-Asset position will trade and evaluate systematic strategies across liquid equities, exchange-traded funds, futures, and foreign exchange. Applicants must live in the local area, which gives the team Pacific Time coverage of late-session behavior, system performance, and research handoffs.

Compensation and Benefits

Base salary: $190,000–$285,000 USD, based on experience
Work arrangement: Fully remote; applicants must be based in the San Francisco, CA area
Experience: 4+ years
Additional compensation: Performance-bonus and equity eligibility based on role and level

About the Role

The central responsibility of the San Francisco, CA opening is live cross-asset exposure, instrument-specific mechanics, funding, rolls, execution, and incident controls. The assigned window includes Pacific Time coverage of late-session behavior, system performance, and research handoffs. Success requires reproducible work, prompt escalation, and clear ownership through review and production use.

San Francisco Operating Focus

The San Francisco opening emphasizes strong quantitative engineering links and critical review before production change. The work combines quantitative review with production discipline during the final hours of the U.S. session. System behavior, data quality, and market evidence are assessed separately before a change is proposed. After the close, the opening prepares technical findings that Eastern Time colleagues can evaluate before the next market day. For this role, that means direct ownership of cross-asset exposure, funding and roll events, execution quality, and venue-specific risk during Pacific Time coverage of late-session behavior, system performance, and research handoffs.

First Review Cycle

The first review cycle for San Francisco, CA starts with Pacific Time coverage of late-session behavior, system performance, and research handoffs. It will establish a measured baseline for cross-asset exposure, funding and roll events, execution quality, and venue-specific risk before the team proposes an operating change. Two assigned tasks anchor the evidence: Review execution quality, funding, rolls, and calendar effects; and Research cross-asset relationships without forcing unstable correlations. The San Francisco opening emphasizes strong quantitative engineering links and critical review before production change. The record must show how each result affected the review. The final record separates completed work, open research, and live operating risk. A reviewer must be able to trace each material decision to live cross-asset exposure, instrument-specific mechanics, funding, rolls, execution, and incident controls.

Responsibilities

• Manage live exposures and instrument-specific risk limits
• Review execution quality, funding, rolls, and calendar effects
• Research cross-asset relationships without forcing unstable correlations
• Lead incident review and operating-control improvements