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Remote Fanuc Robot Programming Jobs in Tennessee

Intuitive

Clinical Sales Manager

Johnson City, TN · On-site +1

We're a team of engineers, clinicians, and innovators united by one purpose: to make surgery ... Remote field management Implementation of sales process Platform and presentation skills Required ...

All JobsRemote Fanuc Robot Programming JobsRemote Fanuc Robot Programming Jobs in Tennessee

Remote Fanuc Robot Programming information

What is the difference between Remote Fanuc Robot Programming vs Remote ABB Robot Programming?

AspectRemote Fanuc Robot ProgrammingRemote ABB Robot Programming
CredentialsTypically requires Fanuc certification or equivalentRequires ABB certification or equivalent
Work EnvironmentPrimarily manufacturing and automation facilities using Fanuc robotsSimilar manufacturing settings with ABB robots
Industry UsageWidely used in automotive, electronics, and industrial automationCommon in automotive, packaging, and industrial sectors

Remote Fanuc Robot Programming and Remote ABB Robot Programming share similar skills, certifications, and work environments, focusing on automation in manufacturing. The main difference lies in the robot brands and specific programming software used. Both roles require technical expertise in robot operation, troubleshooting, and programming, but professionals typically specialize in one brand based on employer needs.

What are the key skills and qualifications needed to thrive as a Remote Fanuc Robot Programmer, and why are they important?

To thrive as a Remote Fanuc Robot Programmer, you need a solid background in robotics, automation engineering, and experience with Fanuc robot controllers, often supported by a relevant technical degree or certification in robotics or industrial automation. Proficiency with Fanuc software (such as Roboguide), PLC integration, and remote troubleshooting tools is typically required. Strong problem-solving abilities, attention to detail, and effective communication are essential soft skills, especially when collaborating with on-site teams from a distance. These skills ensure the efficient setup, maintenance, and optimization of robotic systems, minimizing downtime and supporting seamless remote operations.

What are some common challenges faced when programming Fanuc robots remotely, and how can they be managed?

Remote Fanuc Robot Programming often presents challenges such as limited on-site troubleshooting, network connectivity issues, and communication delays with on-site teams. To manage these, it's important to establish clear protocols for remote access, maintain thorough documentation, and use reliable remote support tools. Close collaboration with on-site operators is essential for testing and implementing changes, and proactive planning can help minimize downtime. Regular virtual meetings and clear communication channels can also ensure that remote programmers stay aligned with the team's goals and safety standards.

What is Remote Fanuc Robot Programming?

Remote Fanuc Robot Programming involves creating, modifying, and troubleshooting programs for Fanuc industrial robots from a remote location, rather than on-site. This process typically utilizes specialized software to connect to the robot's controller over a network, enabling programmers to update code, monitor robot operation, and provide technical support without being physically present. Remote programming can increase efficiency, reduce downtime, and allow experts to assist with complex automation tasks from anywhere in the world.
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Remote Fanuc Robot Programming jobs near you

Artificial Intelligence (AI) Engineer / Developer (Remote)

Statheros

Cookeville, TN • On-site, Remote

Contractor

Posted 21 days ago

Job description

About Us
Statheros is a small DEFTECH firm focused on developing cutting-edge AI and autonomy systems for the US Department of Defense. Our team is passionate about building intelligent systems that solve complex problems. We are looking for a talented AI Engineer specializing in Proximal Policy Optimization (PPO) to lead the development of AI-enabled algorithms that automate the operation of air traffic radar systems.
Job Responsibilities
  • Design, implement, and optimize Proximal Policy Optimization (PPO) algorithms for domain-specific use cases.
  • Develop and train reinforcement learning models for real-world applications, focusing on efficiency and scalability.
  • Collaborate with cross-functional teams to integrate PPO models into production systems.
  • Analyze model performance and experiment with hyperparameter tuning to achieve optimal results.
  • Stay up-to-date with the latest research and advancements in reinforcement learning and apply them to enhance existing solutions.
  • Build robust pipelines for training, evaluation, and deployment of RL models.
  • Document workflows, methodologies, and code for reproducibility and knowledge sharing.
Qualifications
  • Educational Background: Bachelor's or Master's degree in Computer Science, Machine Learning, AI, Mathematics, or related fields. Ph.D. is a plus.
  • Experience:
    • 4+ years of professional experience in machine learning, with a focus on reinforcement learning.
    • Demonstrated expertise in implementing and optimizing PPO or similar reinforcement learning algorithms.
    • Hands-on experience with frameworks like TensorFlow, PyTorch, or JAX.
  • Technical Skills:
    • Strong programming skills in Python; familiarity with Rust or other languages is a plus.
    • Proficiency in designing and running RL experiments in simulated or real-world environments.
    • Experience with distributed training systems for reinforcement learning.
    • Solid understanding of policy gradient methods and reinforcement learning theory.
  • Soft Skills:
    • Excellent problem-solving skills and the ability to work in a collaborative, fast-paced environment.
    • Strong communication skills for presenting findings and collaborating with interdisciplinary teams.
Preferred Qualifications
  • Experience in applying PPO to [specific domain, e.g., robotics, gaming, finance, etc.]
  • Familiarity with OpenAI Gym, RLlib, or other RL development environments
  • Knowledge of parallel computing and GPU acceleration for large-scale RL tasks
What We Offer
  • Remote work location.
  • Competitive salary.
  • Flexible work schedule.
  • Opportunities for professional development and research contributions
  • Access to state-of-the-art resources and tools for AI development.
  • The chance to work on groundbreaking projects with a talented and passionate team.
Employment Type: CONTRACTOR

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