Research Scientist – Human-AI Systems

🕒 Setembro 25

🏄 California, New York – Remoto

infoinfo

💵 $200.000 - $375.000 / ano

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🧬 Cientista Pesquisador(a)

🗣️🇺🇸🇬🇧 Inglês obrigatório

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Vista pela primeira vez pelo Remote Rocketship Setembro 25

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Snorkel AI

51 - 200 funcionários

Fundada em 2019

💼 Consultoria

🏥 Saúde

📦 Logística

Consulting • Healthcare • Logistics

A Snorkel AI é uma plataforma inovadora que se especializa em fornecer dados de treinamento e avaliação de nível especialista, adaptados para modelos de aprendizado de máquina. Seu serviço, conhecido como Expert Data-as-a-Service, permite que as organizações criem conjuntos de dados de alta qualidade para aplicações de IA, acelerando significativamente a entrega de modelos e aprimorando a precisão. Fundada a partir de pesquisas em Stanford, a Snorkel faz parcerias com empresas líderes de IA para expandir os limites das capacidades de IA em diversos setores, incluindo finanças e saúde.

Descrição

• Design, implement, and optimize reusable pipelines combining AI capabilities with expert judgment for data and agentic environment creation • Design and run experiments to validate proof-of-concept approaches and measure effects on data quality, pipeline efficiency, and model performance • Communicate research findings • Partner with engineering, data operations, domain experts, and customers to turn research prototypes into reliable production workflows • Design and test workflows with domain experts for authoring, reviewing, and refining data and environments • Work cross-functionally with data operations, product, and engineering to inform the company roadmap • Stay current with research in data and agentic environment creation and apply best practices • Represent Snorkel's research through publications, blog posts, conference talks, and customer engagements

🎯 Requisitos

• Strong research background in AI, machine learning, NLP, LLMs, or related fields, with experience developing and evaluating new methods • Experience building environments for AI agents in automated research, computer use, coding, or professional domain workflows • Experience with synthetic data generation, human-in-the-loop workflows, reinforcement learning, agent environments, or model evaluation • Strong experimental design skills, including defining hypotheses and conducting ablations • Experience with software engineering best practices, including clean coding, modular design, and version control • Ability to collaborate with domain experts and translate their knowledge into concrete tasks, evaluation criteria, and repeatable workflows • Comfort with rapid iteration, ambiguous research questions, and moving ideas from experimentation into production • Ph.D. in machine learning, NLP, or a related field preferred; equivalent industry or research lab experience considered

🏖️ Benefícios

• Meaningful opportunities to shape priorities and initiatives • Opportunity to influence key strategic decisions and directly impact company success • Support for deepening technical expertise • Leadership opportunities • Opportunities to learn new skills across multiple functions • Career growth, learning, and shared success • Reasonable accommodation for individuals with disabilities • Equal employment opportunities and benefits and privileges of employment

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