AI / ML Engineer

Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills : Computer Vision
Good to have skills : NA
Minimum 15 year(s) of experience is required
Educational Qualification : PhD in Computer Science Mechanical Engineering Robotics Industrial Engineering Electrical Engineering or related discipline
Summary: We are seeking an innovative and highly skilled PhD-level Scientist / Researcher to join our Advanced Technology & Architecture team, driving strategic initiatives in Industrial Digital Transformation. This role is ideal for a candidate with a strong research background and hands-on experience in solving real-world problems in Process and/or Discrete Manufacturing domains. - The ideal candidate will lead cutting-edge research, development, and solution design in areas such as: - Industrial Digital Twins - Physics-based and AI-driven Simulation - Robotics and Autonomous Systems - Industrial AI and Machine Learning - This role will involve close collaboration with industry leaders, ecosystem partners, and internal delivery teams to co-create next-generation solutions that transform manufacturing, industrial operations, and autonomous systems. Roles & Responsibilities: - Lead advanced research and development in Industrial Digital Twins, Simulation, Robotics, and Industrial AI with a focus on solving complex industrial challenges. - Design, prototype, and implement innovative digital twin models and simulation frameworks that enable predictive insights and autonomous decision-making in manufacturing and industrial environments. - Collaborate with cross-functional teams, including Architects, Data Scientists, Software Engineers, and Industry Experts, to design scalable solutions aligned with industry use cases. - Work closely with ecosystem partners (e.g., NVIDIA, Siemens, Microsoft, AWS) and academic institutions to integrate cutting-edge technologies into industrial solutions. - Drive thought leadership by publishing research papers, presenting at industry conferences, and contributing to patents and intellectual property. - Provide technical leadership and mentorship to other scientists, engineers, and solution architects in the team. - Lead PoCs, prototypes, and pilot projects to demonstrate feasibility and business value of industrial AI and digital twin solutions. - Establish best practices, frameworks, and guidelines for development, deployment, and scaling of Industrial Digital Twin and Simulation solutions. - Define and oversee technical roadmap, research priorities, and innovation strategy in line with industry trends. - Strong aptitude for publishing high-impact research papers and presenting findings at international conferences. - Contribution to intellectual property strategy through patents and whitepapers. Professional & Technical Skills: - Deep expertise in Digital Twin technologies, Industrial Simulation, Robotics, and Industrial AI applications. - In-depth understanding of Manufacturing Industry Challenges. - Process Industry: Batch processing, continuous process control, quality monitoring, regulatory compliance (e.g., pharma, chemicals, food & beverage). - Discrete Industry: Factory automation, production line optimization, product lifecycle management, asset monitoring, robotics integration (e.g., automotive, electronics, industrial equipment). - Experience working with Industrial Control Systems (ICS), SCADA systems, MES (Manufacturing Execution Systems), and PLM (Product Lifecycle Management) solutions. - Strong background in mathematical modelling, physics-based simulation, control systems, and machine learning applied to industrial use cases. - Proficient in programming languages such as Python, C++, MATLAB, R, and frameworks like TensorFlow, PyTorch, or equivalent. - Experience in IoT platforms, Industrial Edge Computing, OPC-UA, MQTT, and real-time data integration. - Proven experience applying AI/ML techniques (supervised, unsupervised, reinforcement learning) to industrial use cases, including predictive maintenance, anomaly detection, process optimization, and intelligent automation. - Solid understanding of any cloud platforms: Azure, AWS, or Google Cloud, specifically services related to Industrial AI and Digital Twins. - Good to have experience with NVIDIA Omniverse, Siemens MindSphere, or equivalent Industrial Digital Twin platforms. - Familiarity with industry regulations and standards (e.g., ISA-95, IEC 61508, ISO 55000) and best practices in industrial environments. - Strong analytical and problem-solving skills with ability to translate research into scalable solutions. - Excellent collaboration, communication, and stakeholder management skills. - Active contribution to industry forums, working groups, and think tanks related to Industrial AI and Digital Transformation. - Ability to think strategically about industry trends, disruptive technologies, and future research opportunities. Additional Information: - A 15 years full time education is required.

PhD in Computer Science Mechanical Engineering Robotics Industrial Engineering Electrical Engineering or related discipline

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