Senior / Staff Data Scientist, Applied AI
Clearstreet · Remote
About this role
**Clear Street — Senior / Staff Data Scientist, Applied AI** **About the company** Clear Street is modernizing the brokerage ecosystem. Founded in 2018, the firm is replacing legacy capital markets infrastructure with a cloud-native clearing and custody platform integrated with central clearing houses and exchanges—built to support billions in daily trading volume. **The Team** The Clear Street Active team’s mission is best execution for every asset class in every market. Active is building a new, state-of-the-art, cloud-based trading platform with high-performance access to liquidity venues, advanced charting, and sophisticated order handling for both active traders and institutional workflows. **The Role** You will: - Own the reliability and quality bar for an AI copilot embedded in a trading platform used by sophisticated investors - Design and build evaluation systems to measure correctness, safety, latency, and regression risk across market analysis, portfolio/risk reasoning, and trading workflows (including order placement) - Develop and maintain benchmarks (golden sets, scenario suites, stress/adversarial cases, and continuously refreshed market/regime-based test corpora) - Build automated quality gates and regression workflows that block releases when key metrics degrade - Partner with engineering and product to define safe tool/action contracts (deterministic previews, confirmations, auditability) and ensure predictable assistant behavior - Own model improvement loops tied to evals (data collection/labeling strategies, error taxonomy, prompt/tooling changes, and—when appropriate—fine-tuning or preference optimization) - Design and operate monitoring + incident response for AI (telemetry, alerting, RCA, and fix-forward processes) - Develop deep understanding of trading concepts (margin, shorting, portfolio margin, risk, execution) and communicate them accurately to users **Tech Stack** Rust, TypeScript, Postgres, React (Web), React Native (Mobile), observability/telemetry tooling, LLM APIs + model serving, eval/training pipelines **Requirements** - 8+ years of experience shipping production software; strong proficiency with at least one programming language - Strong CS 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 benchmark impact) - Ability to define metrics, build measurement pipelines, and drive decisions from data - Comfort working across the stack (debugging model/tooling failures, instrumenting services, partnering on UX patterns that improve safety and trust) - High self-motivation and willingness to jump into unfamiliar areas **Bonus** - 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 and margin types - Experience with Rust and performance-sensitive services - Experience designing incident response and SLOs for ML/AI systems **Compensation & Benefits** - Base salary range: **$200,000 – $500,000** (base only; excludes bonus/equity) - Competitive compe
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