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Computational Modeling Simulation Multiphysics Jobs in Chula Vista, CA

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Computational Modeling Simulation Multiphysics information

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$149.3K

How much do computational modeling simulation multiphysics jobs pay per year?

As of Aug 20, 2026, the average yearly pay for computational modeling simulation multiphysics in Chula Vista, CA is $104,961.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,400.00 and $134,200.00 per year, depending on experience, location, and employer.

What is computational modeling simulation multiphysics?

Computational modeling simulation multiphysics refers to the use of computer-based models to simulate and analyze systems that involve multiple interacting physical phenomena—such as fluid dynamics, heat transfer, electromagnetics, and structural mechanics—all at once. This approach allows researchers and engineers to predict complex real-world behavior, optimize designs, and reduce the need for expensive prototypes. Multiphysics simulations are widely used in industries like aerospace, automotive, energy, and biomedical engineering, where accurate modeling of coupled physical processes is critical.

What are common challenges faced by professionals in computational modeling simulation multiphysics, and how can they be addressed?

One of the main challenges in Computational Modeling Simulation Multiphysics roles is managing the complexity of integrating multiple physical phenomena, such as thermal, structural, and fluid dynamics, into a single simulation. This often requires a deep understanding of both the underlying physics and the numerical methods used by simulation software. Collaborating closely with domain experts and maintaining clear communication within multidisciplinary teams can help address these challenges. Additionally, staying updated with advances in simulation tools and best practices through continuous learning is key to overcoming technical hurdles and ensuring accurate results.

What are the key skills and qualifications needed to thrive as a computational modeling simulation multiphysics engineer, and why are they important?

A strong background in physics, engineering, mathematics, and computational science—typically with an advanced degree—is essential for a Computational Modeling Simulation Multiphysics Engineer. Proficiency in simulation software such as ANSYS, COMSOL Multiphysics, MATLAB, and programming languages like Python or C++ is commonly required, along with familiarity with high-performance computing environments. Analytical thinking, problem-solving skills, and effective communication set standout professionals apart in this field. These capabilities enable accurate modeling of complex physical phenomena, efficient collaboration, and successful project outcomes in research and industry settings.

What is the difference between Computational Modeling Simulation Multiphysics vs Computational Engineer?

AspectComputational Modeling Simulation MultiphysicsComputational Engineer
CredentialsTypically requires degrees in engineering, physics, or related fields; certifications in simulation software are commonSimilar educational background; often holds engineering degrees and software certifications
Work EnvironmentPrimarily in R&D labs, engineering firms, or manufacturing settings focusing on complex simulationsInvolved in product development, software development, or systems design in various industries
Industry UsageUsed in aerospace, automotive, energy, and manufacturing for advanced simulationsApplied across industries for designing, analyzing, and optimizing systems and products

While both roles involve computational skills and engineering principles, Computational Modeling Simulation Multiphysics specializes in complex, multi-physics simulations, whereas Computational Engineer focuses on designing and implementing computational solutions across various engineering projects.

What cities near Chula Vista, CA are hiring for Computational Modeling Simulation Multiphysics jobs?

Cities near Chula Vista, CA with the most Computational Modeling Simulation Multiphysics job openings:

Senior Staff Software Engineer, AI Platforms

Murata Manufacturing Co., Ltd.

San Diego, CA • On-site

$209 - $272/hr

Other

Posted 2 days ago

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Senior Staff Software Engineer, AI Platforms

Location: San Diego, CA, US

pSemi Corporation is a Murata company driving semiconductor integration. pSemi builds on Peregrine Semiconductor’s 30-year legacy of technology advancements and strong IP portfolio but with a new mission—to enhance Murata’s world-class capabilities with high-performance semiconductors. With a strong foundation in RF integration, pSemi’s product portfolio now spans power management, connected sensors, optical transceivers, antenna tuning and RF frontends. These intelligent and efficient semiconductors enable advanced modules for smartphones, base stations, personal computers, electric vehicles, data centers, IoT devices and healthcare. From headquarters in San Diego and offices around the world, pSemi’s team explores new ways to make electronics for the connected world smaller, thinner, faster and better.

Job Summary

As a Senior Staff Software Engineer focused on AI platforms, you will provide end-to-end technical leadership for the software systems that enable AI-assisted RFIC design and verification workflows. Your primary mandate will be to define and build the platform through which AI-enabled applications and intelligent agents safely interact with engineering tools, data, and computational infrastructure. You will architect scalable systems spanning user experiences, backend services, distributed workflows, engineering data, secure execution environments, and cloud or hybrid infrastructure.

This role is centered on systems engineering, platform architecture, and productionaization rather than foundational model research or model training. With significant autonomy, you will establish technical direction, convert emerging prototypes into dependable multi-user products, and create reusable platform capabilities that can support multiple engineering applications. You will remain hands‑on while influencing architecture across teams, reducing systemic technical risk, and driving solutions from concept through deployment, operations, and continuous improvement. This is a senior individual contributor role for an expert engineer who can help build the software foundation for next‑generation semiconductor innovation, including 5G and beyond.

This position has responsibility for:
  • Own the architecture and evolution of distributed software platforms that support AI-enabled engineering workflows. Define service boundaries, APIs, data flows, execution models, asynchronous processing patterns, and platform standards that can be reused across multiple products and teams. Establish a multi-year technical direction while balancing near‑term delivery, maintainability, security, and operational risk.
  • Design and productionize systems that incorporate generative AI, LLM services, intelligent agents, retrieval, tool‑driven automation, and human approval workflows. Focus on reliability, evaluation, traceability, failure handling, policy enforcement, and secure execution rather than model research or training. Create common patterns that allow new AI capabilities and engineering tools to be integrated efficiently and safely.
  • Architect, implement, and maintain end-to-end software products spanning modern web applications, backend services, APIs, real‑time interactions, and engineering integrations. Establish scalable design patterns that enable teams to deliver intuitive, maintainable, and reliable user experiences while remaining hands‑on in critical areas of the codebase.
  • Design, automate, and continuously improve development, testing, deployment, and production environments across AWS, Microsoft Azure, Google Cloud Platform, on‑premises infrastructure, or hybrid environments. Establish robust practices for containerization, Kubernetes or comparable orchestration, infrastructure as code, CI/CD, configuration management, release automation, networking, storage, and environment promotion.
  • Lead the development of secure, resilient, and production‑ready systems with strong observability, fault tolerance, recovery, and operational support. Define standards for identity and access management, authorization, secrets and credential management, workload isolation, auditability, monitoring, incident response, root‑cause analysis, and service‑level objectives.
  • Collaborate across software, infrastructure, AI, and RFIC engineering teams to automate workflows involving design, simulation, testbench configuration, job execution, data collection, analysis, verification, and report generation. Integrate AI-enabled capabilities with EDA tools and computational environments in ways that are safe, reproducible, traceable, and usable by engineers.
  • Direct the design of data architectures and integration patterns that connect applications, databases, engineering tools, AI services, enterprise systems, and long‑running computational workloads. Ensure data is reliable, secure, discoverable, and accessible, and establish resilient orchestration patterns for queued, asynchronous, and failure‑prone workflows.
  • Serve as a technical authority across multiple products and engineering disciplines. Lead architectural reviews, resolve complex cross‑system challenges, make build‑versus‑buy and platform‑standardization decisions, identify and retire systemic technical risk, establish engineering standards, and mentor other engineers. Drive alignment through technical judgment and influence rather than reporting authority.
  • Independently investigate emerging software, cloud, AI platform, infrastructure, and developer‑platform technologies. Identify practical opportunities to apply them within semiconductor engineering and produce clear architecture, design, operational, decision, and roadmap documentation that supports alignment, adoption, and long‑term maintainability.
Minimum Qualifications (Experience and Skills)
  • Typically requires 10+ years of progressive, hands‑on software engineering experience, including technical leadership of complex, production-scale systems and broad impact across multiple teams or product areas.
  • Demonstrated expertise in designing, building, deploying, and operating distributed software platforms across multiple layers of the application stack, including user‑facing applications, APIs, backend services, data systems, workflow systems, and infrastructure.
  • Strong knowledge of distributed systems, API design, data modeling, asynchronous processing, messaging, system integration, fault tolerance, security, reliability, and production operations.
  • Experience deploying and operating production workloads in at least one major cloud platform, such as AWS, Microsoft Azure, or Google Cloud Platform, with practical knowledge of networking, compute, storage, identity, security, and managed services.
  • Experience with containerized applications, Kubernetes or comparable orchestration platforms, CI/CD, infrastructure as code, configuration management, environment promotion, monitoring, and incident response.
  • Experience designing secure multi‑user systems, including identity and access management, authorization, secrets and credential management, workload isolation, audit logs, and operational controls.
  • Experience integrating AI/ML services, LLM APIs, intelligent automation, or other nondeterministic components into production software systems. Expertise in training foundation models is not required.
  • Experience defining technical direction and leading cross‑functional teams through architecture, implementation, deployment, migration, and continuous improvement of complex products.
  • Exceptional written and verbal communication skills, with a proven ability to document and present technical designs, decisions, risks, tradeoffs, and roadmaps to technical and nontechnical stakeholders.
  • Track record of independent, high‑impact contributions that improve product capabilities, engineering velocity, system reliability, platform reuse, or organizational effectiveness.
Education Requirements
  • Bachelor’s degree in Computer Engineering, Computer Science, Electrical Engineering, or a related technical field. A master’s degree in Computer Engineering, Computer Science, Data Science, Electrical Engineering, or a related technical field is preferred.

This job operates in a professional office environment. This role routinely uses standard office equipment.

Physical Demands

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is regularly required to talk or hear. The employee frequently is required to stand; walk; use hands to finger, handle or feel; and reach with hands and arms. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception and ability to adjust focus. This position requires the ability to occasionally lift office products and supplies, up to 20 pounds.

USD 208,851.58 - 271,522.09 per year

pSemi Corporation supports a diverse workforce and is committed to a policy of equal employment opportunity for applicants and employees. pSemi does not discriminate on the basis of age, race, color, religion (including religious dress and grooming practices), sex/gender (including pregnancy, childbirth, or related medical conditions or breastfeeding), gender identity, gender expression, genetic information, national origin (including language use restrictions and possession of a driver’s license issued under Vehicle Code section 12801.9), ancestry, physical or mental disability, legally‑protected medical condition, military or veteran status (including “protected veterans” under applicable affirmative action laws), marital status, sexual orientation, or any other basis protected by local, state or federal laws applicable to the Company. pSemi also prohibits discrimination based on the perception that an employee or applicant has any of those characteristics, or is associated with a person who has or is perceived as having any of those characteristics.

Note: The Peregrine Semiconductor name, Peregrine Semiconductor logoand UltraCMOS are registered trademarks and the pSemi name, pSemi logo, HaRP andDuNE are trademarks of pSemi Corporation in the U.S. and other countries. All other trademarks are the property of their respective companies. pSemi products are protected under one or more of the following U.S. Patents: http://patents.psemi.com

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