jazzhr
Autonomous Learning Engineer
Bright Vision Technologies
Remote, USA
Full-time
Senior · 10+ years experience
Remote
USD 130000-180000 yearly / year
Discovered Yesterday
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Role Overview
Bright Vision Technologies is seeking a highly experienced Autonomous Learning Engineer with 10+ years of experience in Artificial Intelligence, Reinforcement Learning (RL), and Deep Learning to design, train, and deploy intelligent decision-making systems for complex real-world applications. The ideal candidate will possess deep expertise in Python, reinforcement learning, deep learning, simulation environments, distributed training, and RLHF (Reinforcement Learning from Human Feedback) while driving the architecture and deployment of scalable, production-ready autonomous learning solutions.
Key Skills for This Role
PythonPyTorchTensorFlowJAXRay RLlibStable-Baselines3
Full Job Posting
Location
- 100% Remote (U.S.) Position Type: Full-time, Direct W2 Salary Range: $130,000–$180,000 Annually Experience Required: 10+ Years
- Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary
Bright Vision Technologies is seeking a highly experienced Autonomous Learning Engineer with 10+ years of experience in Artificial Intelligence, Reinforcement Learning (RL), and Deep Learning to design, train, and deploy intelligent decision-making systems for complex real-world applications. The ideal candidate will possess deep expertise in Python, reinforcement learning, deep learning, simulation environments, distributed training, and RLHF (Reinforcement Learning from Human Feedback) while driving the architecture and deployment of scalable, production-ready autonomous learning solutions.
Key Responsibilities
- Design, develop, and deploy advanced reinforcement learning solutions for complex decision-making and autonomous systems.
- Architect scalable reinforcement learning training pipelines using distributed computing and GPU-accelerated infrastructure.
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