Robotics Trainer Jobs (NOW HIRING)

Robotics & AI Research Engineer
Description
Auzmor is redefining workforce training by seamlessly integrating human and robotic skill development to empower the hybrid workforce of tomorrow. As a Robotics & AI Research Engineer in our Robotics Division, you will lead pioneering research to enhance robotic capabilities through advanced artificial intelligence, focusing on areas such as autonomous decision-making, object recognition, and natural language processing for human-robot interaction. You will develop state-of-the-art machine learning models, reinforcement learning algorithms, and computer vision solutions to drive Auzmor's end-to-end hybrid workforce training platform. Collaborating with robotics software, simulation, and compliance teams, you will create AI-driven training modules, proprietary algorithms, and skill development tools, ensuring robust integration with robotic systems for applications in manufacturing, logistics, and healthcare.
This role is essential to achieving Auzmor's mission of delivering 25% improvement in human-robot efficiency, addressing the 35% skills gap in human-robot collaboration, and maintaining a 2-3 year lead in the $45B robotic training market by 2028, growing to $100B by 2030.
Key Responsibilities
• AI Model Development: Design, train, and optimize advanced machine learning models, including deep learning, reinforcement learning, and generative AI, for robotic applications such as autonomous navigation, dynamic grasping, or conversational human-robot interfaces.
• Research Innovation: Conduct cutting-edge research in computer vision, neural policies, or natural language processing to develop adaptive and deterministic robotic behaviors for tasks like inventory scanning or patient assistance.
• Skill Creation: Develop AI-driven training modules and templates for Auzmor's no-code Task Creator UI, enabling enterprise clients to create task-specific robotic skills (e.g., quality control in manufacturing, patient care in healthcare).
• Simulation and Validation: Validate AI models in NVIDIA Isaac Sim environments (e.g., warehouse, hospital scenarios), targeting 95% task success and 0.1% collision rates; support real-world validation during pilot deployments with enterprise clients.
• Fleet Monitoring Integration: Create algorithms for real-time anomaly detection and continuous learning, integrating with AWS IoT Greengrass to address 5% failure rates and enable updates to neural policies and behavior trees for fleet optimization.
• Compliance Alignment: Ensure AI models comply with OSHA, EU AI Act, and ISO 10218 standards, supporting digital badge generation for audit-ready compliance records in regulated industries.
• Knowledge Dissemination: Publish research findings in top-tier journals or internal whitepapers to enhance Auzmor's thought leadership, and develop proprietary algorithms to strengthen our intellectual property portfolio.
• Cross-functional collaboration: Partner with robotics software engineers to translate research into production-ready systems, collaborate with simulation teams to refine scenarios, and work with enterprise clients to customize AI solutions for pilot programs.
Requirements
• Education: PhD or Master's degree in Artificial Intelligence, Machine Learning, Robotics, Computer Science, or a related field.
• Experience:
• 2+ years of experience in AI research applied to robotics, autonomous systems, or related fields.
• Proven expertise in machine learning frameworks such as PyTorch, TensorFlow, or JAX.
• Strong publication record in peer-reviewed journals or demonstrated experience deploying AI models in real-world robotic applications.
• Experience with ROS 2, computer vision libraries (e.g., OpenCV), or simulation platforms (e.g., NVIDIA Isaac Sim) is highly desirable.
• Technical Skills:
• Advanced knowledge of reinforcement learning, computer vision, or natural language processing for robotic applications.
• Proficiency in designing and optimizing neural policies, behavior trees, or generative AI models for adaptive robotic tasks.
• Ability to develop algorithms for real-time decision-making and scalable human-robot collaboration.
• Soft Skills: Exceptional analytical and creative problem-solving skills, strong communication skills to convey complex research to diverse audiences, and the ability to collaborate across technical and client-facing teams.
• Preferred: Experience in robotics applications for manufacturing, logistics, or healthcare; familiarity with compliance standards (OSHA, EU AI Act, ISO 10218); prior work on hybrid human-robot training or fleet management systems.
Why Needed
The Robotics & AI Research Engineer is a cornerstone of Auzmor's Robotics Division, driving the development of AI innovations that power our end-to-end hybrid workforce training platform. This role directly supports Auzmor's Phase 2 (2025) goals of launching AI agent training modules, Task Creator prototypes, and robotic training pilots, as well as Phase 3 (2026) objectives of full-scale neural policy deployment and anomaly detection. By addressing the 35% skills gap in human-robot collaboration and enabling 99% fleet uptime, this position aligns with Auzmor's vision to capture a share of the $45B robotic training market by 2028, growing to $100B by 2030.
Why Auzmor?
• Impact: Be part of a 2-3 year lead in hybrid workforce training, working with 100+ enterprise clients, including Fortune 500 companies.
• Innovation: Leverage Auzmor's 6-year AI/ML stack, ROS 2-compatible platform, and partnerships with NVIDIA and AWS to build state-of-the-art robotics solutions.
• Growth: Join a team targeting $18M ARR in 2025 and $27.2M by 2028, with opportunities to shape a rapidly expanding industry.
• Culture: Collaborate with a dream team, including our CPO and VP of Robotics, in a dynamic, mission-driven environment.
Location
Des Moines, Iowa, USA
Compensation
Competitive salary, equity options, and comprehensive benefits
Auzmor is an equal-opportunity employer committed to diversity and inclusion. We encourage applications from all qualified candidates.