Job description

We Are: At Ansys, Part of Synopsys, we’re the global leader in engineering simulation software, helping innovative companies solve complex design challenges. Our cutting-edge solutions power advancements across industries, from aerospace to consumer electronics. Join us and help shape the future of technology. You Are: You are a highly motivated engineer who thrives at the intersection of engineering simulation, data-driven methods, and AI/ML-enabled workflows. Your expertise allows you to operate confidently in customer-facing environments, translating complex, multidisciplinary challenges into scalable, practical solutions. You possess a strong foundation in simulation or engineering systems, hands-on experience with machine learning and automation, and the ability to engage as a trusted technical advisor. You are energized by ambiguity, seeking out opportunities to enable new ways of working through automation, digital twins, and intelligent simulation workflows. You are passionate about democratizing simulation technology, making advanced capabilities accessible to a broader spectrum of users. Your approach is both strategic and hands-on, balancing high-level vision with detailed technical execution. You excel in collaborative environments, working closely with cross-functional teams and customers to deliver impactful solutions. You advocate for innovation and continuous improvement, mentoring peers and championing best practices. Your communication skills enable you to distill complex concepts into actionable insights, fostering understanding across diverse audiences. Above all, you are driven by the desire to make a tangible impact in the world of engineering and technology. What You’ll Be Doing: • 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,validatenew 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. • Mentor team members and contribute to the best internal practices around AI, automation, and simulation integration. The Impact You Will Have: • 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. What You’ll Need: • 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 tooperateeffectively 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. • Demonstratedexpertiseapplying 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 You Are: • 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. Rewards and Benefits: We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process. At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability. In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a competitive total rewards package. The actual compensation offered will be based on a number of job-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request. The base salary range for this role is across the U.S.

Requirements

Must-haves

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,validatenew 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.
Mentor team members and contribute to the best internal practices around AI, automation, and simulation integration.
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.
MS (or PhD) in Engineering, Computer Science, Applied Mathematics, or related field .
5+ years of experience in engineering systems, simulation, or data-driven modeling.
Experience working with modeling, simulation, optimization, or data-driven engineering workflows.
Strong analytical, problem-solving, and communication skills.
Ability tooperateeffectively 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.
Demonstratedexpertiseapplying machine learning techniques in engineering contexts, including surrogate modeling, regression methods, or neural networks (CNNs, RNNs, autoencoders).

Nice-to-haves

Strong programming skills (Python preferred).

Application prep

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Keywords to mirror

aimlmachine learningpythonkubernetesawsazurego

Platform: avature
Effort: medium

Benefits

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Vision

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