Senior / Staff AI Model Engineer

Role Description

The mission of the Clear Street Active team is to provide best execution for every asset class in every market. Active is currently building a new, state-of-the-art, cloud-based trading platform providing high-performance traders access to liquidity venues across multiple asset classes, cutting-edge charting capabilities, and sophisticated order handling with the flexibility to service both the active trader and institutional workflows.

• You will own the reliability and quality bar for an AI copilot embedded in a trading platform used by sophisticated investors.
• You will design and build evaluation systems that measure correctness, safety, latency, and regression risk across market analysis, portfolio/risk reasoning, and trading workflows (including order placement).
• You will develop and maintain benchmarks: curated “golden sets,” scenario suites, stress/adversarial cases, and continuously refreshed market/regime-based test corpora.
• You will build automated quality gates and regression workflows that block releases when key metrics degrade.
• You will partner with engineering and product to define safe tool/action contracts (deterministic previews, confirmations, auditability) and ensure predictable assistant behavior.
• You will own model improvement loops tied to evals: data collection/labeling strategies, error taxonomy, prompt/tooling changes, and when appropriate, fine-tuning or preference optimization to measurably improve benchmark performance.
• You will design and operate monitoring + incident response for AI: telemetry, alerting, RCA, and “fix-forward” processes.
• You will develop a deep understanding of trading concepts (margin, shorting, portfolio margin, risk, execution) and how to express them accurately and understandably to users.

Qualifications

• At least Eight (8) years of experience shipping production software; strong proficiency with any programming language.
• Strong knowledge of computer science fundamentals, testing methodology, and systems design.
• Experience building evaluation frameworks, test harnesses, and benchmark suites for complex systems (LLMs/agents/search/retrieval/ranking/recommenders).
• Experience running model improvement cycles: dataset curation, labeling/QA, offline experimentation, and deploying changes with measurable impact on benchmarks.
• Ability to define metrics, build measurement pipelines, and drive engineering/product decisions from data.
• Comfort working across the stack: debugging model/tooling failures, instrumenting services, and partnering with frontend/product on UX patterns that improve safety and trust.
• High degree of self-motivation and willingness to jump into unfamiliar areas to solve problems.

Requirements

• Experience with fine-tuning, preference optimization, distillation, or prompt/compiler-style techniques for improving tool-use reliability.
• Experience creating domain-specific benchmarks and adversarial suites (e.g., “known-bad” scenarios) for high-stakes applications.
• Deep experience with trading across asset classes, margin types, etc.
• Experience with Rust and performance-sensitive services.
• Experience designing incident response and SLOs for ML/AI systems.

Benefits

• The Base Salary Range for this role is $200,000 - $350,000.
• Competitive compensation packages, company equity, 401k matching, gender neutral parental leave, and full medical, dental and vision insurance.
• In-office benefits include lunch stipends, fully stocked kitchens, happy hours, a great location, and amazing views.
• A culture that promotes collaboration and celebrates each other's successes.
• Commitment to diversity in ideas, cultures, and experiences.