1 час назад
Research Engineer (AI)
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 Engineer (AI): Building and deploying production-scale reinforcement learning environments, data curation systems, and evaluation pipelines for training AI agents with an accent on applied research, scalable infrastructure, and customer-specific environment design. Focus on translating recent RL research into robust production systems, creating automated quality assurance and evaluation frameworks, and collaborating with frontier AI labs and enterprise customers.
Location: Hybrid in Mountain View, CA
Company
is an applied AI research lab focused on data and reinforcement learning environment curation for training and evaluating agents.
What you will do
- Partner with frontier AI labs and enterprise customers to understand agent training needs and design custom environments.
- Prototype approaches to environment generation, curriculum design, data curation, and agent evaluation.
- Build scalable systems for creating, validating, and deploying reinforcement learning environments.
- Develop automated quality assurance pipelines and evaluation frameworks for measuring environment effectiveness.
- Scale research prototypes into production systems, establish reproducible workflows, and optimize performance.
- Present research findings and provide technical guidance to research teams, customers, and other stakeholders.
Requirements
- MS or PhD in Machine Learning, Computer Science, or a related field, or equivalent industry research experience.
- Research contributions through publications, open-source projects, or deployed research systems.
- Deep understanding of reinforcement learning, agent training, or related areas, with the ability to implement ideas from recent papers.
- Strong Python skills and experience with ML frameworks such as PyTorch or JAX.
- Experience building production systems or research infrastructure at scale, including cloud platforms such as GCP or AWS and distributed computing.
- Strong communication, project scoping, prioritization, testing, validation, and quality assurance skills.
Nice to have
- Hands-on experience with RL agent training or evaluation systems.
- Background in data-centric AI, synthetic data generation, or dataset creation.
- Publications in leading ML/AI conferences such as NeurIPS, ICML, or ICLR.
- Experience in research engineering or applied science roles.
- Contributions to widely used datasets, benchmarks, or evaluation suites.
Culture & Benefits
- Full-time hybrid work in Mountain View, California.
- Direct collaboration with leading AI research labs and enterprise partners.
- Health coverage.
- Competitive salary and equity.
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