Autonomous Learning Engineer

About the role

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. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Location: 100% Remote (U.S.) | Position Type: Full-time, Direct W2 | Salary Range: $130,000–$180,000 Annually

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.

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
• Design, build, and optimize simulation environments for training and validating reinforcement learning agents
• Develop, implement, and evaluate modern RL algorithms, reward models, and policy optimization techniques
• Build autonomous learning systems leveraging RLHF, imitation learning, offline reinforcement learning, and multi-agent learning approaches
• Improve model convergence, sample efficiency, training stability, inference performance, and production scalability
• Integrate reinforcement learning models into production applications while ensuring reliability, safety, monitoring, and continuous improvement
• Collaborate with AI researchers, data scientists, software engineers, and product teams to deliver enterprise-scale AI solutions
• Mentor engineers and provide technical leadership on reinforcement learning architecture, experimentation, and engineering best practices
• Evaluate emerging reinforcement learning frameworks, algorithms, and research to drive continuous innovation

Requirements

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Robotics, Mathematics, or a related technical discipline
• 10+ years of professional experience in Artificial Intelligence, Machine Learning, Deep Learning, or Reinforcement Learning
• Expert-level programming skills in Python and extensive experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX
• Strong experience with reinforcement learning libraries such as Ray RLlib, Stable-Baselines3, CleanRL, or Acme
• Hands-on experience developing simulation environments using tools such as Gymnasium/OpenAI Gym, Isaac Sim, MuJoCo, Unity ML-Agents, or NVIDIA Omniverse
• Experience with distributed training, GPU acceleration, model optimization, and large-scale AI infrastructure
• Strong understanding of reinforcement learning theory, optimization, probability, stochastic processes, and decision-making algorithms
• Experience deploying AI solutions on cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP)
• Excellent analytical, communication, collaboration, and technical leadership skills

Preferred Qualifications

• Experience with RLHF, multi-agent reinforcement learning, robotics, autonomous systems, or control systems
• Hands-on experience with foundation models, LLM alignment, agentic AI, or autonomous AI agents
• Experience with MLOps, Kubernetes, Docker, CI/CD pipelines, and production AI deployment
• Publications in top AI conferences, open-source contributions, patents, or recognized technical leadership in reinforcement learning
• Knowledge of Responsible AI, AI safety, model governance, explainability, and regulatory compliance
• Ph.D. or Master's degree specializing in Artificial Intelligence, Machine Learning, Reinforcement Learning, Robotics, or Control Systems

Pay

$130,000–$180,000 Annually