Senior Autonomous Learning Engineer - Remote

Bright Vision Technologies; Raleigh (NC); On-site; USD 130,000 - 180,000; Full time

Job summary

Bright Vision Technologies is seeking an 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.

Qualifications

• 10+ years of professional experience in AI/ML/RL.
• Expert-level programming in Python and DL frameworks.
• Experience deploying RL models in production.

Responsibilities

• Design, develop, and deploy reinforcement learning solutions for autonomous systems.
• Architect scalable RL training pipelines with distributed computing and GPUs.
• Build, simulate, and validate training environments for RL agents.
• Develop RL algorithms, reward models, and policy optimization techniques.
• Incorporate RLHF, imitation learning, and multi-agent learning into production systems.
• Improve convergence, sample efficiency, and deployment performance.
• Integrate RL models into production apps with reliability and safety.
• Collaborate with AI researchers, data scientists, and engineers across teams.
• Mentor engineers on RL architecture and best practices.
• Evaluate new RL frameworks and research to drive innovation.

Skills

Python

Reinforcement Learning

Deep Learning

Communication

Education

Bachelor's or Master's in CS/AI/ML/Robotics/Math

PhD or Master’s in AI/ML/RL/Robotics/Control Systems

Tools

PyTorch

TensorFlow

JAX

Ray RLlib

Stable-Baselines3

Gymnasium/OpenAI Gym

MuJoCo

Unity ML-Agents

NVIDIA Omniverse

AWS

Azure

GCP

Job description

Bright Vision Technologies is seeking an 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.