Senior Applied Scientist (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Senior Applied Scientist (AI): Designing and implementing scalable neuro-symbolic systems that integrate formal reasoning with GenAI for intelligent automation with an accent on reliability and verifiability. Focus on enhancing agentic AI capabilities, solving hallucination detection, and advancing the state of the art in automated reasoning.
Location: USA, CA, Santa Clara
Salary: $192,200 – $260,000 annually
Company
The world-leading provider of cloud services building next-generation models for intelligent automation.
What you will do
- Design and implement production-grade neuro-symbolic systems integrating formal reasoning with GenAI.
- Collaborate cross-functionally to translate customer pain points into scalable AI features.
- Extend formal reasoning capabilities for hallucination detection and policy verification.
- Own the end-to-end science lifecycle from research and experimentation to production deployment.
- Mentor junior scientists and engineers to foster a culture of scientific rigor.
- Advance the state of the art through publications at top-tier venues and patents.
Requirements
- PhD, or Master's degree with 5+ years of applied research experience.
- Proficiency in programming with Java, C++, Python, or related languages.
- Must be based in or authorized to work in the USA (Santa Clara, CA).
Nice to have
- Experience in formal verification, program analysis, or constraint-solving.
- Expertise in SMT solver implementation or code-reasoning languages like Lean.
- Experience with autonomous agents, API orchestration, or large multimodal models.
Culture & Benefits
- Comprehensive health insurance including medical, dental, and vision coverage.
- Financial perks including 401(k) matching, RSUs, and sign-on payments.
- Inclusive team culture with employee-led affinity groups and diversity events.
- Focus on work-life harmony and flexibility in the working culture.
- Access to world-class computational resources and massive datasets.
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