13 дней назад
Research Scientist - Human-AI Systems (AI)
200 000 - 375 000$
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Research Scientist - Human-AI Systems (AI): Building reusable pipelines and environments that combine AI capabilities, automated generation, real-world data, and human expert input with an accent on agentic environments, data quality, and frontier model performance. Focus on designing rigorous experiments, translating research prototypes into production workflows, and creating repeatable systems for domain experts to author and evaluate data.
Location: Hybrid in San Francisco or New York, with a remote option; US-based locations are specified.
Salary: $200,000–$375,000 USD per year.
Company
Snorkel AI develops data-centric AI solutions that help enterprises transform expert knowledge into specialized, production-ready AI systems.
What you will do
- Design, implement, and optimize reusable pipelines combining AI capabilities, real-world data, automated generation, and expert judgment.
- Build and expand data and agentic environments targeting frontier model performance gaps.
- Design rigorous experiments, define evaluation methods, run ablations, and measure data quality, pipeline efficiency, and model performance.
- Collaborate with engineering, data operations, domain experts, academic partners, customers, and product teams to convert research prototypes into production workflows.
- Design workflows that help domain experts author, review, and refine data and AI environments.
- Represent research through publications, blog posts, conference talks, and customer engagements.
Requirements
- Strong research background in AI, machine learning, NLP, LLMs, or a related field, including 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 hypothesis definition and ablation studies.
- Software engineering experience with 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; a Ph.D. in machine learning, NLP, or a related field is preferred.
Culture & Benefits
- Work in a rapidly scaling company with market-proven solutions and robust funding.
- Opportunity to shape priorities, influence strategic decisions, and contribute directly to company growth.
- Support for technical development, leadership exploration, and cross-functional learning.
- Commitment to equal employment opportunity, diversity, and reasonable workplace accommodations.
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