Robotics / Machine Learning Engineer designing AI-driven solutions for renewable energy projects. Engage in multidisciplinary collaboration to develop autonomous systems and intelligent applications.
Responsibilities
Design and develop AI agents that automate engineering workflows, particularly hydraulic studies for renewable energy projects (runoff analysis, water flow modeling, infrastructure dimensioning)
Build and train machine learning models in Python (TensorFlow / PyTorch) for computer vision, sensor fusion, and environmental monitoring
Integrate Vision-Language Models (VLMs) and foundation models such as NVIDIA Cosmos into multimodal AI applications
Work with Earth Observation data, remote sensing pipelines, and geospatial tools (Google Earth Engine, ArcGIS, QGIS)
Develop and automate hydrological models (HEC-HMS, HEC-RAS)
Use NVIDIA PhysX and IsaacSim / IsaacLab to build physically accurate simulations and digital twins
Contribute to ROS2-based robotic systems (training provided if needed)
Collaborate closely with robotics, AI, and environmental engineers to deliver integrated, production-ready solutions
Requirements
Strong background in Machine Learning and Computer Vision
Advanced Python development skills
Experience with ML frameworks (TensorFlow or PyTorch)
Familiarity with geospatial analysis or environmental modeling
Ability to work across AI systems, simulations, and engineering workflows
Strong problem-solving skills and structured thinking
Nice to have: Experience with robotics systems
Knowledge of ROS2
Experience with hydrological modeling tools
Exposure to simulation environments (PhysX, IsaacSim)
Benefits
Hybrid office set up / Remote work
Competitive compensation package
Group medical health insurance plan
The opportunity to experiment and learn a cutting-edge AI technologies
Work on cutting-edge AI and robotics projects with real-world impact
Build autonomous systems for renewable energy and environmental applications
Opportunity to shape next-generation AI-driven robotics with real-world impact
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