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Strong Tier-1 brand and popular AI title balanced by niche robotics and sim-to-real specialization.
Role requires domain-specific robotics, simulation, and industrial safety expertise, limiting cross-industry transferability.
Many mandatory technical requirements for production ML, robotics integration, sim-to-real, and MLOps create strict filters.
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Design, train, evaluate, and deploy AI models for autonomous and semi-autonomous robotic workflows spanning simulation and real-world environments.
Build and operate data and training pipelines, apply sim-to-real methods, and integrate AI models with Digital Twin and robotics platforms for production-grade systems.
Deploy scalable inference and control services on cloud and edge using containers and Kubernetes; establish observability and monitoring for reliable industrial deployment.
Bachelor’s or master’s degree in computer science, AI, Robotics, Electrical Engineering, or related field.
Experience building, training, evaluating, and deploying AI/ML systems in production.
Strong Python engineering skills; experience with deep learning frameworks like PyTorch and computer vision or multimodal model development.
Experience with robotic AI concepts (perception, planning, control integration, imitation or reinforcement learning, Vision-Language-Action models).
Operates effectively at the intersection of robotics, industrial software, and AI to deliver reliable, observable, and scalable systems.
Experienced in applying sim-to-real methods and integrating AI models with Digital Twin platforms such as NVIDIA Isaac Sim.
Has practical MLOps skills including experiment tracking, model versioning, CI/CD, and deployment on cloud and edge infrastructures.