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Entry Level Modeling Simulation Engineer Jobs in Boston, MA

SES

Computational Materials Scientist

Woburn, MA · On-site +1

$180K - $200K/yr

... Engineering, or a closely related computational/physics field. * Core Simulation Expertise: Deep and extensive experience in atomistic simulation and quantum modeling, including proficiency with key ...

ARM

Staff Software Modeling Engineer

Waltham, MA · On-site

$198K - $268K/yr

Experience with programmer's view modeling, instruction-level simulators (e.g. QEMU, Simics, Gem5 ... Virtualizer), or SoC virtual prototyping using C++, SystemC, or TLM. * Experience with low-level ...

ARM

Staff Software Modeling Engineer

Waltham, MA · Hybrid

$198K - $268K/yr

Experience with programmer's view modeling, instruction-level simulators (e.g. QEMU, Simics, Gem5 ... Virtualizer), or SoC virtual prototyping using C++, SystemC, or TLM. * Experience with low-level ...

COMSOL

Applications Engineer: Acoustics

Burlington, MA · On-site

Training and Mentoring • Develop your technical and simulation knowledge and abilities through ... modeling acoustic applications based on numerical methods, such as the finite element method or ...

MIT Lincoln Laboratory

RF Engineer

Lexington, MA · Hybrid

Execute modeling, simulation, and analysis of phased array antennas and RF subsystems. Perform ... Master's degree in electrical engineering, physics, applied mathematics, computer science, or a ...

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All JobsModeling Simulation Engineer JobsEntry Level Modeling Simulation Engineer JobsEntry Level Modeling Simulation Engineer Jobs in Boston, MA

Entry Level Modeling Simulation Engineer information

See Boston, MA salary details

$42.4K

$134.1K

$207K

How much do entry level modeling simulation engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for entry level modeling simulation engineer in Boston, MA is $134,061.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,900.00 and $159,200.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Modeling Simulation Engineer vs Mechanical Design Engineer?

AspectEntry Level Modeling Simulation EngineerMechanical Design Engineer
Required CredentialsBachelor's in Mechanical, Aerospace, or related fields; basic knowledge of simulation softwareBachelor's in Mechanical or Aerospace Engineering; CAD and design software skills
Work EnvironmentResearch labs, engineering teams, simulation software environmentsDesign studios, manufacturing facilities, engineering departments
Employer & Industry UsageAutomotive, aerospace, defense, manufacturing companiesProduct design firms, manufacturing companies, R&D departments

While both roles require a background in mechanical engineering and involve technical skills, the Entry Level Modeling Simulation Engineer focuses on creating and analyzing virtual models using simulation software, whereas the Mechanical Design Engineer emphasizes designing physical components and systems. Both roles are essential in product development but differ in their primary tasks and tools used.

What kinds of projects and collaboration can I expect as an Entry Level Modeling Simulation Engineer?

As an Entry Level Modeling Simulation Engineer, you'll typically work on projects involving the creation, testing, and validation of simulation models for systems or products. You'll collaborate closely with senior engineers, software developers, and sometimes project managers to ensure model accuracy and integration into larger projects. Expect to contribute by running simulations, analyzing data, and preparing reports, while learning industry-standard tools and methodologies. The work environment is often team-oriented, with regular meetings to discuss progress and troubleshoot challenges together.

What is an Entry Level Modeling Simulation Engineer?

An Entry Level Modeling Simulation Engineer is a professional who uses computer models and simulations to analyze, test, and improve systems or products, often in fields like aerospace, automotive, or manufacturing. They typically work with software tools to create virtual representations of real-world processes, enabling companies to predict outcomes and optimize designs before physical prototypes are built. This role is ideal for recent graduates or those new to the industry, providing foundational experience in engineering analysis and problem-solving. Responsibilities may include developing simulation models, validating results, and collaborating with senior engineers and other departments.

What are the key skills and qualifications needed to thrive as an Entry Level Modeling Simulation Engineer, and why are they important?

To thrive as an Entry Level Modeling Simulation Engineer, you need a solid background in mathematics, physics, and computer science, usually supported by a relevant engineering or STEM degree. Familiarity with simulation software (like MATLAB or Simulink), programming languages (such as Python or C++), and version control systems is often required. Strong problem-solving abilities, attention to detail, and effective teamwork help set you apart in this role. These skills ensure accurate model development, effective collaboration, and the ability to solve complex real-world engineering problems.
What are the most commonly searched types of Modeling Simulation Engineer jobs in Boston, MA? The most popular types of Modeling Simulation Engineer jobs in Boston, MA are:
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Entry Level Modeling Simulation Engineer jobs near you
Computational Materials Scientist

Computational Materials Scientist

SES

Woburn, MA • On-site, Remote

$180K - $200K/yr

Full-time

Medical

Re-posted 10 days ago

Job description

SES AI Corp. (NYSE: SES) is dedicated to accelerating the world's energy transition through groundbreaking material discovery and advanced battery management. We are at the forefront of revolutionizing battery creation, pioneering the integration of cutting-edge machine learning into our research and development. Our AI-enhanced, high-energy-density and high-power-density Li-Metal and Li-ion batteries are unique; they are the first in the world to utilize electrolyte materials discovered by AI. This powerful combination of "AI for science" and material engineering enables batteries that can be used across various applications, including transportation (land and air), energy storage, robotics, and drones.
To learn more about us, please visit: www.ses.ai
What We Offer:
  • A highly competitive salary and robust benefits package, including comprehensive health coverage and an attractive equity/stock options program within our NYSE-listed company.
  • The opportunity to contribute directly to a meaningful scientific project-accelerating the global energy transition-with a clear and broad public impact.
  • Work in a dynamic, collaborative, and innovative environment at the intersection of AI and material science, driving the next generation of battery technology.
  • Significant opportunities for professional growth and career development as you work alongside leading experts in AI, R&D, and engineering.
  • Access to state-of-the-art facilities and proprietary technologies are used to discover and deploy AI-enhanced battery solutions.

What we Need:
The SES AI Prometheus team isseeking an exceptional Computational Materials Scientist to combine physics-based simulation (DFT, MD, quantum modeling) with AI-assisted material prediction to generate high-quality training data and accelerate materials discovery. This role is crucial for advancing our understanding of electrochemical energy materials at the atomic level. As a Computational Materials Scientist, you will be a core data-driven modeler responsible for executing and automating complex simulations.
Essential Duties and Responsibilities:
  • Atomistic Modeling & Simulation
  • Conduct and oversee DFT (Density Functional Theory), MD (Molecular Dynamics), and QM (Quantum Mechanics) simulations of battery components, including electrolytes, coatings, and electrodes.
  • Develop and refine ML-enhanced force fields and surrogate models to accelerate simulation time scales and enable multi-scale simulation efforts.
  • Apply expertise in atomistic simulation and quantum modeling to solve key challenges in electrochemical energy materials (e.g., batteries/fuel cells).
  • AI Data Generation & Prediction
  • Generate high-quality, structured simulation data to serve as training sets for AI property prediction models and material screening modules.
  • Contribute to the development of battery domain LLM features and advanced property-prediction models.
  • Automate complex simulation workflows using strong coding practices to enhance efficiency and scalability.
  • Collaboration & Tooling
  • Collaborate with experimental teams, leveraging a hybrid computational + experimental literacy to validate models and drive design iteration.
  • Utilize advanced simulation tools (VASP, Quantum Espresso) and data science libraries (TensorFlow, Pandas) to manage and analyze large datasets.

Education and/or Experience:
  • Education: Ph.D. in Mechanical Engineering, Materials Science, Chemical Engineering, or a closely related computational/physics field.
  • Core Simulation Expertise: Deep and extensive experience in atomistic simulation and quantum modeling, including proficiency with key QM/DFT tools (VASP, Quantum Espresso) and MD simulations.
  • Domain Focus: Strong background in electrochemical energy materials and extensive computational work focused on batteries/fuel cells.
  • Coding Proficiency: Strong coding skills in Python (along with related libraries like Pandas and TensorFlow) for simulation workflow automation and data analysis.
  • ML Application: Experience in developing or utilizing ML-enhanced force fields and surrogate models for materials prediction., or equivalent practical experience.

Preferred Qualifications:
  • LLM Development: Experience in developing battery domain LLM features or property-prediction models.
  • Hybrid Skillset: Demonstrated experience working in a hybrid computational + experimental environment.
  • Tooling Diversity: Familiarity with additional data analysis tools like R, SQL, MATLAB, and time-series forecasting libraries like Prophet.
  • Target Background: Previous experience at national laboratories, XtalPi, Entalpic, or deep battery modeling groups.

The salary range for this position as required under applicable pay transparency laws.
Salary Range
$180,000-$200,000 USD

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