# Staff Engineer – AI/ML & Digital Twin **Company**: Ansys, Part of Synopsys **Location**: United States **Work arrangement**: remote **Experience**: staff **Job type**: Employee **Salary**: $112000-$168000 **Category**: Engineering **Industry**: Technology **Apply**: https://careers.synopsys.com/job/canonsburg/staff-engineer-ai-ml-and-digital-twin/44408/93512568768?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_019ba3f3-88c ## Description ### Job Description We are seeking a highly motivated Staff Engineer to join our team, focusing on AI/ML and Digital Twin technologies. As a Staff Engineer, you will lead and execute technical engagements across the customer lifecycle, including discovery, solution development, demonstrations, evaluations, and deployment. ### Responsibilities - Lead and execute technical engagements across the customer lifecycle, including discovery, solution development, demonstrations, evaluations, and deployment. - Engage directly with customers to understand engineering workflows, data availability, and decision-making processes, translating them into AI-enabled simulation and digital engineering solutions. - Develop and implement differentiated solutions using technologies such as automation, reduced order modeling, optimization, simulation democratization, system-level modeling, and digital twins. - Integrate machine learning models within simulation and digital twin pipelines to improve prediction accuracy, reduce computational cost, and enable near real-time insights. - Define and deliver automated and scalable workflows that reduce reliance on expert-driven simulation and enable broader adoption across engineering teams. - Lead or contribute to first-of-a-kind or ambiguous use cases, including AI-assisted design exploration, surrogate modeling, and digital twin deployment. - Collaborate closely with product development teams to influence roadmap, validate new capabilities, and improve usability of AI-enabled features. - Deliver professional services, training, and technical guidance to ensure successful adoption of advanced workflows. - Support pre-sales and technical marketing activities through demonstrations, evaluations, and industry engagement. ### Benefits - Enable customers to transition from traditional simulation to AI-augmented and automated engineering workflows. - Reduce time-to-insight through surrogate modeling, optimization, and intelligent automation. - Expand access to simulation by supporting democratization across engineering and non-expert users. - Drive adoption of digital twin technologies for predictive and operational decision-making. - Influence product direction by connecting real-world use cases with next-generation AI-enabled capabilities. - Contribute to business growth through high-impact technical engagements and solution delivery. ### Requirements - MS (or PhD) in Engineering, Computer Science, Applied Mathematics, or related field. - 5+ years of experience in engineering systems, simulation, or data-driven modeling. - Strong programming skills (Python preferred). - Experience working with modeling, simulation, optimization, or data-driven engineering workflows. - Strong analytical, problem-solving, and communication skills. - Ability to operate effectively in a customer-facing, consultative engineering role. - Proven experience in automation of engineering workflows or pipelines using tools such as optiSLang, modeFrontier, HEEDS or equivalent. - Demonstrated expertise applying machine learning techniques in engineering contexts, including surrogate modeling, regression methods, or neural networks (CNNs, RNNs, autoencoders). - Understanding of projection-based ROMs, dimensionality reduction, and feature engineering. - Knowledge of multi-fidelity system modeling using Twin Builder, Simulink, AMESim or equivalent. - Familiarity with deployment and operationalization of AI models, including integration into engineering workflows and use of frameworks such as PyTorch, TensorFlow, scikit-learn, Kubernetes, AWS/Azure equivalent. - Exposure to cloud or HPC-based environments for large-scale simulation or data processing. ### Who We Are Looking For - Customer-focused and able to build trusted relationships. - Comfortable working in ambiguous, fast-evolving technical environments. - A strong communicator who can translate complex concepts into actionable insights. - Self-driven, organized, and capable of managing multiple priorities. - A collaborative team player who contributes to a culture of learning and innovation. ### The Team You’ll Be A Part Of You will be part of a multidisciplinary engineering team focused on advancing industry adoption of simulation through AI, automation, digital twin, and MBSE technologies. The team collaborates closely with customers, product development, and go-to-market functions to deliver innovative, high-impact solutions. ## Skills ### Required - Python - Automation - Reduced Order Modeling - Optimization - Simulation Democratization - System-Level Modeling - Digital Twins - Machine Learning - Surrogate Modeling - Regression Methods - Neural Networks - Projection-Based ROMs - Dimensionality Reduction - Feature Engineering - Multi-Fidelity System Modeling - Cloud or HPC-Based Environments --- Source: [Apply at careers.synopsys.com](https://careers.synopsys.com/job/canonsburg/staff-engineer-ai-ml-and-digital-twin/44408/93512568768?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)