Digital Twin Developer

Tasks As a Digital Twin Developer, you will be responsible for designing, developing, and implementing digital twin models that simulate real-world systems and processes. You will collaborate with cross-functional teams to envision manufacturing process. You would be responsible to optimize manufacturing processes and improve planning efficiency through integration of digital twin in Core Process at MO. Key Responsibilities: Digital Twin Development: Design, develop, and maintain digital twin models for automotive systems, ensuring their scalability and reliability. Integration and Collaboration: Work closely with engineering teams to integrate digital twins into product development cycles. Data Analysis: Analyze digital twin data to extract actionable insights for optimizing processes. Trend Monitoring: Stay informed about the latest trends and technologies in digital twin development. 3D Workflows: Develop and demonstrate 3D workflows using NVIDIA Omniverse, with expertise in complex 3D pipelines and content creation workflows. GPU Development: Utilize GPUs to develop SDKs and full-stack datacenter architecture. Software Architecture: Design and develop software technology architecture tailored to client needs. DCC Tools Expertise: Experience with DCC tools such as 3ds Max, Maya, Revit, Blender, and Substance. Interactive 3D Pipeline: Knowledge of the full interactive 3D pipeline, from modeling to application, within manufacturing industries. DevOps and Cloud: Develop software in hybrid cloud environments, combining cloud and on-prem solutions. Data Manipulation: Passion for manipulating and translating 3D geometry, animation, and materials into code. Technical Expertise: Broad and deep technical knowledge across infrastructure requirements, development, design, and re-engineering. Machine Learning: Familiarity with machine learning and deep learning techniques. Generative AI: Understanding of generative AI technologies and implementation. Qualifications Bachelors or masters degree in computer science, Engineering, or a related field. Proven experience in digital twin development or similar simulation technologies. Proficiency in programming languages such as Python, C#, C++, or Java. Familiarity with IoT, data analytics, and cloud computing. Strong problem-solving skills and attention to detail. Excellent communication and teamwork abilities. Tasks As a Digital Twin Developer, you will be responsible for designing, developing, and implementing digital twin models that simulate real-world systems and processes. You will collaborate with cross-functional teams to envision manufacturing process. You would be responsible to optimize manufacturing processes and improve planning efficiency through integration of digital twin in Core Process at MO. Key Responsibilities: Digital Twin Development: Design, develop, and maintain digital twin models for automotive systems, ensuring their scalability and reliability. Integration and Collaboration: Work closely with engineering teams to integrate digital twins into product development cycles. Data Analysis: Analyze digital twin data to extract actionable insights for optimizing processes. Trend Monitoring: Stay informed about the latest trends and technologies in digital twin development. 3D Workflows: Develop and demonstrate 3D workflows using NVIDIA Omniverse, with expertise in complex 3D pipelines and content creation workflows. GPU Development: Utilize GPUs to develop SDKs and full-stack datacenter architecture. Software Architecture: Design and develop software technology architecture tailored to client needs. DCC Tools Expertise: Experience with DCC tools such as 3ds Max, Maya, Revit, Blender, and Substance. Interactive 3D Pipeline: Knowledge of the full interactive 3D pipeline, from modeling to application, within manufacturing industries. DevOps and Cloud: Develop software in hybrid cloud environments, combining cloud and on-prem solutions. Data Manipulation: Passion for manipulating and translating 3D geometry, animation, and materials into code. Technical Expertise: Broad and deep technical knowledge across infrastructure requirements, development, design, and re-engineering. Machine Learning: Familiarity with machine learning and deep learning techniques. Generative AI: Understanding of generative AI technologies and implementation. Qualifications Bachelors or masters degree in computer science, Engineering, or a related field. Proven experience in digital twin development or similar simulation technologies. Proficiency in programming languages such as Python, C#, C++, or Java. Familiarity with IoT, data analytics, and cloud computing. Strong problem-solving skills and attention to detail. Excellent communication and teamwork abilities.