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Model Behavior Engineer – Reasoning and Decision Making

🕒 vor 24 Tagen

🏄 California – Remote

infoinfo

💵 $220.000 - $320.000 / Jahr

⏰ Vollzeit

🟡 Mittelstufe

🟠 Senior

👷🏻‍♀️ Ingenieur

🗣️🇺🇸🇬🇧 Englisch erforderlich

Woher diese Stelle stammt

Veröffentlicht auf der Karriereseite von Elicit, nicht über eine Jobbörse

Von Remote Rocketship zum ersten Mal gesehen vor 24 Tagen

Noch offen auf der Website von Elicit. Geprüft vor 46 Minuten.

Logo of Elicit

Elicit

11 - 50 Mitarbeiter

Gegründet 2023

📚 Bildung

🤖 Künstliche Intelligenz

⚕️ Krankenversicherung

Education • Artificial Intelligence • Healthcare Insurance

Elicit ist ein Tool zur Verbesserung der Produktivität in der akademischen Forschung, indem es die Analyse von Forschungsarbeiten automatisiert. Es ermöglicht Nutzern, Arbeiten zusammenzufassen, Daten zu extrahieren und Ergebnisse schnell und effizient zu synthetisieren, was den Prozess der Literaturrecherche erheblich beschleunigt und organisiert. Mit dem Zugang zu über 125 Millionen Forschungsarbeiten unterstützt Elicit Forscher dabei, relevante Literatur mithilfe von Anfragen in natürlicher Sprache zu entdecken und bietet Funktionen, die systematische Übersichten und Meta-Analysen vereinfachen.

Beschreibung

• Understand decisions users and domain experts need to make in scientific R&D and commercial strategy • Identify objectives, constraints, available evidence, and important unknowns • Define and measure good reasoning using example inspection, expert judgment, and quantitative analysis • Build evaluations for underspecified problems and validate that scores reflect meaningful improvements • Investigate model and agent failures and turn observations into testable hypotheses • Experiment with problem decomposition, context, tools, information-seeking, and self-checking approaches • Design agent environments and representations for problems, evidence, assumptions, and unresolved questions • Design reliable software abstractions, data structures, and component boundaries for reasoning workflows and evaluations • Balance simplicity, flexibility, reliability, latency, and cost • Write maintainable code and participate in design and code reviews • Test, monitor, diagnose, and integrate systems into the product • Collaborate with engineers, product, design, and domain experts • Take problems from investigation and experimental design through implementation and product use • Improve systems built around existing frontier models, with training or finetuning where useful

🎯 Anforderungen

• Rigorous thinking about ambiguous problems, including identifying hidden assumptions and weighing conflicting evidence • Curiosity across domains and ability to learn unfamiliar subjects • Clear communication with people of different expertise • Ability to devise useful experiments without established benchmarks • Ability to inspect failures in detail and distinguish evidence from noise • Ability to independently write and debug code • Experience working with data and model APIs • Comfortable with Python or a comparable programming language • Practical familiarity with language models and their capabilities and limitations • Strong engineering and architectural judgment • Experience building understandable, usable, and extensible software • Effective use of coding assistants while verifying the resulting design and code • Evidence through substantial projects, thoughtful experiments, and clear technical explanations • Ability to travel for quarterly retreats and in-person coworking events • Role optimized for candidates contributing at senior L4 level or above

🏖️ Vorteile

• Flexible work environment with office or remote work • Quarterly team retreats and coworking events • Fully covered health, dental, vision, and life insurance for the employee • Generous family insurance coverage • FSA/HSA • Flexible vacation policy with a minimum recommendation of 20 days/year • Company holidays • $200 monthly wellbeing stipend • 401K with a 6% employer match • New Mac and $1,000 workstation/home office budget in the first year • $500 workstation/home office budget every year thereafter • $1,000 quarterly AI Experimentation & Learning budget • Team administrative assistant for personal and work tasks • Above-market equity with employee-friendly equity terms

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