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Compact Device Modeling Jobs (NOW HIRING)

EP RN

Centralia, IA ยท On-site

... device (CIED) models of pacemakers, ICDs and Implantable Loop Recorders (ILRs) and documents ... or compact state. โ€ข Valid Iowa Driver's/Chauffeurs License required, must meet Mercy's Motor ...

Senior/Principal Scientist (Theory)

Everett, WA ยท On-site

$130K - $160K/yr

... and compact, modular systems, Zap is building the foundational technologies needed to deploy the ... Collaborate with experimental teams to harness modeling insights to guide device design and ...

Working knowledge of at least one of: photonic device physics, circuits, signal processing, or statistical analysis. * Prior work on compact models, SPICE-like simulators, or link/yield statistical ...

Sr. Engineer, Research Software

San Jose, CA ยท On-site

$170K - $192K/yr

Working knowledge of at least one of: photonic device physics, circuits, signal processing, or statistical analysis. * Prior work on compact models, SPICE-like simulators, or link/yield statistical ...

... in a compact form-factor, thus enabling the next-generation of optical health sensors...The ... The candidate must be able to employ simulation tools to develop models of sensor behavior. Lastly ...

... in a compact form-factor, thus enabling the next-generation of optical health sensors...The ... The candidate must be able to employ simulation tools to develop models of sensor behavior. Lastly ...

... models (e.g., mechanical, electro-mechanical, fluid dynamics) to simulate device behavior and ... The company's SuperSwitch is an ultra-low power consumption, high radix, compact chip-scale design ...

... models (e.g., mechanical, electro-mechanical, fluid dynamics) to simulate device behavior and ... The company's SuperSwitch is an ultra-low power consumption, high radix, compact chip-scale design ...

Senior MEMS Design Engineer

Santa Clara, CA ยท On-site

$180K - $260K/yr

... models (e.g., mechanical, electro-mechanical, fluid dynamics) to simulate device behavior and ... The company's SuperSwitch is an ultra-low power consumption, high radix, compact chip-scale design ...

Sr. Heat Exchanger Engineer

El Segundo, CA ยท On-site

$165K - $180K/yr

Lead in-house design and development of advanced compact heat exchangers, including printed circuit ... models to test data. * Collaborate closely with thermodynamic cycle analysts, mechanical systems ...

... device (CIED) models of pacemakers, ICDs and Implantable Loop Recorders (ILRs) and documents ... or compact state. ยท Valid Iowa Driver's/Chauffeurs License required, must meet Mercy's Motor ...

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Compact Device Modeling information

What are the key skills and qualifications needed to thrive as a Compact Device Modeling Engineer, and why are they important?

To thrive as a Compact Device Modeling Engineer, you need a strong background in semiconductor physics, device modeling, and typically an advanced degree in electrical engineering or a related field. Proficiency with simulation tools like SPICE, TCAD software, and programming languages such as Python or MATLAB, as well as knowledge of industry-standard modeling languages (e.g., Verilog-A), is essential. Strong analytical thinking, attention to detail, and effective communication skills help you collaborate with cross-functional teams and interpret complex data. These skills are crucial for developing accurate models that drive innovation and reliability in semiconductor device design.

What types of teams or departments does a Compact Device Modeling engineer typically collaborate with?

Compact Device Modeling engineers often work closely with circuit design teams, process technology groups, and EDA (Electronic Design Automation) tool developers. Collaboration is essential because accurate device models are critical for reliable circuit simulations and successful chip fabrication. Regular communication with these departments ensures that the models reflect real-world device behavior and are compatible with evolving design requirements and manufacturing technologies. This cross-functional teamwork provides valuable exposure to multiple aspects of semiconductor development and can open doors for broader career growth.

What is compact device modeling?

Compact device modeling is the process of creating simplified mathematical models that accurately represent the electrical behavior of semiconductor devices, such as transistors, within electronic circuits. These models are essential for circuit simulation tools, enabling engineers to predict circuit performance without resorting to complex, time-consuming physical simulations. Compact models balance accuracy and computational efficiency, making them a cornerstone in the design and verification of integrated circuits.

What is the difference between Compact Device Modeling vs Semiconductor Device Engineer?

AspectCompact Device ModelingSemiconductor Device Engineer
CredentialsTypically requires engineering degree, specialized modeling certificationsRequires engineering degree, often with additional certifications in device physics
Work EnvironmentResearch labs, simulation centers, R&D departmentsDesign labs, manufacturing facilities, R&D teams
Industry UsageUsed for device simulation, circuit design, and performance predictionInvolved in device development, fabrication, and testing

Compact Device Modeling focuses on creating simplified models of semiconductor devices for simulation purposes, aiding circuit design. Semiconductor Device Engineers work on designing, developing, and testing actual semiconductor devices. While both roles require engineering expertise and involve semiconductor technology, modeling is more simulation-oriented, whereas engineering involves hands-on device development.

More about Compact Device Modeling jobs
What cities are hiring for Compact Device Modeling jobs? Cities with the most Compact Device Modeling job openings:
What states have the most Compact Device Modeling jobs? States with the most job openings for Compact Device Modeling jobs include:
Infographic showing various Compact Device Modeling job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 92% In-person, and 8% Hybrid job distribution.

Senior Materials and Surface Science Engineer

nEye.ai

Santa Clara, CA

$122.70K - $168.50K/yr

Full-time

Posted 29 days ago


Job description

About us

nEye.ai, a well-funded optical switch startup, is poised to revolutionize the future of data centers. nEyeโ€™s MEMS-based silicon photonics optical circuit switches (OCS) eliminate critical bottlenecks in AI processing by enabling direct optical connections among thousands of GPUs and memory units. The company's OCS is an ultra-low power consumption, high radix, compact chip-scale design, offering hyperscale data centers enhanced performance, efficiency, and scalability.

Job Overview

We are looking for a senior individual contributor with deep expertise in materials science and surface chemistry as it applies to semiconductor fabrication and optical systems.

This role is critical to understanding and improving how fabrication processes at the material and interface level impact optical performance in our silicon photonics devices.

You will work across design, process, and test to analyze, diagnose, and improve material interfaces, thin films, and surface interactions that directly affect device behavior, reliability, and yield.

Key Responsibilities
  • Investigate how surface chemistry and material interfaces in silicon-based photonic and MEMS material systems impact performance

  • Analyze effects of etching, deposition, oxidation, and plasma processes on surface states, morphology, and optical mechanisms

  • Partner with design and process teams to translate material-level insights into improved device performance and manufacturability

  • Lead investigations connecting fabrication outcomes to device-level optical and mechanical performance

  • Design and interpret experiments involving thin films, interfaces, and surface treatments (e.g., passivation, cleaning, annealing)

  • Collaborate with fabrication partners on process evaluation and optimization

  • Utilize and guide characterization efforts using techniques such as SEM, TEM, AFM, XPS, ellipsometry, SIMS, etc.

  • Develop models or frameworks that connect process to material properties and optical outcomes

Required Qualifications
  • PhD in Materials Science, Applied Physics, Electrical Engineering, or related field

  • 7 - 15+ years of experience in semiconductor, photonics, or adjacent advanced materials environments

  • Deep understanding of surface chemistry and interface physics in semiconductor systems

  • Expertise in dielectric and semiconductor thin films and metallization.

  • Strong knowledge of plasma processes, etching, deposition, oxidation, and their impact on materials

  • Strong intuition for how material properties affect optical phenomena

  • Experience working in or closely with semiconductor fabs / foundries

  • Hands-on experience with failure analysis and materials characterization techniques

Nice to Have Skills
  • Direct experience with silicon photonics or optical devices

  • Familiarity with waveguides, optical interfaces, or photonic integration

  • Experience in MEMS fabrication or integration

  • Background in process development or integration engineering

  • Exposure to modeling optical-material interactions

Starting salary and title will depend on, and be commensurate with, relevant industry experience, skills, training, education, market demands, and the ultimate job duties and requirements.
nEye.ai is an Equal Opportunity Employer.ย All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.