Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Низкая зарплатаАутсорс-модельПередовой стекТрендовый доменЧеткие требования
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
RL Engineer (AI): Designing, training, and deploying reinforcement-learning systems for high-impact decision-making with an accent on reward modeling, simulation environments, and policy training at scale. Focus on training neural-network policies on GPU clusters, evaluating production systems for stability and safety, and translating RL research into deployable solutions.
Location: 100% remote within the United States
Salary: $80,000–$100,000 annually
Company
hirify.global is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
What you will do
Design, train, and deploy reinforcement-learning systems for complex decision-making problems.
Develop and tune reward functions for non-trivial environments.
Build and use simulation environments and large-scale experience-collection pipelines.
Train and evaluate neural-network policies on GPU clusters.
Move RL solutions from research into production with a focus on stability, safety, and continuous improvement.
Communicate technical findings and contribute to impactful RL work through shipped systems or publications.
Requirements
Master’s or PhD in Computer Science, Machine Learning, or a related field, or equivalent applied experience.
Six or more years of combined reinforcement-learning research and engineering experience.
Strong proficiency in Python and modern deep-learning frameworks.
Hands-on experience with a major RL library or an in-house RL stack.
Understanding of probability, optimization, and the theoretical foundations of reinforcement learning.
Eligible to work in the United States; new H-1B visa petitions cannot be sponsored.
Nice to have
Experience with RLHF for large language models.
Familiarity with multi-agent or hierarchical reinforcement learning.
Exposure to robotics, control systems, or autonomous driving.
Publications in RL or related research venues.
Open-source contributions to RL libraries or environments.
Culture & Benefits
Full-time direct W2 employment.
Remote work within the United States.
Career growth opportunities within an established technology organization.
Equal employment opportunity and a workplace free from harassment and discrimination.
Hiring process
Submit a resume for consideration.
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