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Autonomous Learning Engineer

Job in Fishers, Hamilton County, Indiana, 46085, USA
Listing for: Bright Vision Technologies
Full Time position
Listed on 2026-10-09
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 130000 - 180000 USD Yearly USD 130000.00 180000.00 YEAR
Job Description & How to Apply Below

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Job Title

Autonomous Learning Engineer

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.
  • 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.
Required Qualifications
  • 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, Tensor Flow, 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, Mu Jo Co , 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
    ,…
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