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Entry Level Computational Engineering Jobs (NOW HIRING)

NTT Data, Inc.

5277 - Mechanical Engineer L1

$84K - $117K/yr

Your role at a glance As an Entry-level Mechanical Engineer at NTT Global Data Centers Americas ... Computational Fluid Dynamics (CFD) tools. • Strong analytical and problem-solving skills.

GAI Consultants

Bridge Engineer

Canton, OH

GAI Consultants, Inc is seeking an entry-level engineer to work out of our Canton, OH office within ... Geometric and computational proficiency. * Ability to communicate in technical writing and ...

GAI Consultants

Bridge Engineer

Columbus, OH

GAI Consultants, Inc is seeking an entry-level engineer to work out of our Canton, OH office within ... Geometric and computational proficiency. * Ability to communicate in technical writing and ...

GAI Consultants

Bridge Engineer

Columbus, OH

GAI Consultants, Inc is seeking an entry-level engineer to work out of our Canton, OH office within ... Geometric and computational proficiency. * Ability to communicate in technical writing and ...

GAI Consultants

Bridge Engineer

Columbus, OH · On-site

GAI Consultants, Inc is seeking an entry-level engineer to work out of our Canton, OH office within ... Geometric and computational proficiency. * Ability to communicate in technical writing and ...

GAI Consultants

Bridge Engineer

Canton, OH · On-site

GAI Consultants, Inc is seeking an entry-level engineer to work out of our Canton, OH office within ... Geometric and computational proficiency. * Ability to communicate in technical writing and ...

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All JobsEntry Level Computational Engineering Jobs

Entry Level Computational Engineering information

See salary details

$48.5K

$121.5K

$137.5K

How much do entry level computational engineering jobs pay per year?

As of Jun 26, 2026, the average yearly pay for entry level computational engineering in the United States is $121,515.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $131,500.00 per year, depending on experience, location, and employer.

How to get into computational engineering?

To enter computational engineering, candidates typically need a bachelor's degree in engineering, computer science, or a related field. Developing skills in programming languages such as Python or C++, understanding numerical methods, and gaining experience with simulation software or data analysis tools are essential. Internships, project work, and certifications can also improve job prospects in this field.

What is the difference between Entry Level Computational Engineering vs Entry Level Mechanical Engineering?

AspectEntry Level Computational EngineeringEntry Level Mechanical Engineering
Required CredentialsBachelor's in Computational Engineering, Computer Science, or related fieldBachelor's in Mechanical Engineering or related field
Work EnvironmentSoftware development, simulation, modeling in labs or officesDesign, testing, manufacturing in labs, factories, or offices
Industry UsageTech, aerospace, automotive, research institutionsManufacturing, automotive, aerospace, energy sectors
Common Search/ComparisonYesYes

Entry Level Computational Engineering focuses on software, simulations, and modeling using programming skills, often in tech and research industries. Entry Level Mechanical Engineering emphasizes physical design, testing, and manufacturing processes. Both roles require a bachelor's degree but differ in daily tasks and industry applications, with computational roles leaning toward software and mechanical roles toward physical systems.

What engineers make $500,000?

Highly experienced engineers in specialized fields such as petroleum engineering, aerospace engineering, or certain senior roles in software engineering can earn $500,000 or more annually, often through a combination of base salary, bonuses, and stock options. These positions typically require advanced skills, extensive experience, and sometimes leadership responsibilities or working in high-demand industries.

What engineers make $300,000 a year?

Highly experienced engineers in specialized fields such as software engineering, petroleum engineering, or aerospace engineering can reach annual salaries of $300,000 or more, often through senior roles, bonuses, or stock options. These positions typically require advanced skills, extensive experience, and sometimes professional certifications or advanced degrees.

Is computational engineering in demand?

Computational engineering is in high demand across industries such as aerospace, automotive, and energy, as it involves using advanced modeling, simulation, and programming skills to solve complex problems. Entry-level roles often require knowledge of programming languages like Python or C++ and familiarity with simulation tools, making it a valuable and growing field for new graduates.
More about Entry Level Computational Engineering jobs
What cities are hiring for Entry Level Computational Engineering jobs? Cities with the most Entry Level Computational Engineering job openings:
What are the most commonly searched types of Computational Engineering jobs? The most popular types of Computational Engineering jobs are:
What job categories do people searching Entry Level Computational Engineering jobs look for? The top searched job categories for Entry Level Computational Engineering jobs are:
Entry Level Computational Engineering jobs near you
Infographic showing various Entry Level Computational Engineering job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $121,515 per year, or $58.4 per hour.
2026 Graduate - Synthetic Aperture Radar ML Engineer - Imaging Systems

2026 Graduate - Synthetic Aperture Radar ML Engineer - Imaging Systems

Johns Hopkins Applied Physics Laboratory

Laurel, MD • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago

Johns Hopkins Applied Physics Laboratory rating

9.9

Company rating: 9.9 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

1st of 58 rated research

Job description

Description
Are you passionate about machine learning, edge processing, and synthetic aperture radar imaging?
Do you seek a position to apply your engineering skills in an innovative and collaborative laboratory environment?
If so, we are looking for someone like you to join our team at the Johns Hopkins University Applied Physics Laboratory (APL)!
We are seeking an entry-level engineer or scientist to support the growth of RF/machine learning capabilities. The selected candidate will contribute in two primary areas: optimization of SAR-related processing for GPU-enabled edge hardware, and support of machine learning workflows including curated dataset development, model training, evaluation, and deployment to edge devices. This role is intended for a candidate with strong technical fundamentals and the potential to grow into a broader RF/ML contributor through mentorship and hands-on experience. Deep SAR expertise is not required.
As a member of our team, you will...
  • Support development and optimization of SAR-related algorithms and processing workflows for execution on GPU-enabled edge hardware.
  • Assist with profiling, debugging, and improving computational performance to meet edge-device constraints such as latency, memory, throughput, and power.
  • Build, organize, and maintain curated datasets for machine learning training, validation, and testing.
  • Develop and apply data preprocessing, labeling, and quality-check workflows to prepare data for analysis and model development.
  • Train, evaluate, and help refine machine learning models for deployment in edge or resource-constrained environments.
  • Support integration and deployment of algorithms and trained models onto edge computing platforms.
  • Collaborate with senior staff to transition prototypes into robust, testable implementations.
  • Document technical approaches, results, implementation details, and performance tradeoffs.
  • Work closely with mentors and team members to grow technical depth in RF, SAR, machine learning, and edge deployment applications.
  • Contribute to the team's emerging RF/ML capabilities through applied development, experimentation, and technical learning.

Qualifications
You meet our minimum qualifications if you have...
  • Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or relevant field.
  • Foundation in signal processing, linear algebra, and related applied mathematical methods.
  • Programming experience in Python, C++, or similar languages for technical computing, data processing, or algorithm development.
  • Familiarity with basic machine learning workflows, including data preparation, model training, evaluation, and performance assessment.
  • Ability to work with raw and processed data to create organized, curated datasets for analysis and model development.
  • Interest in performance optimization of computational pipelines, including familiarity with GPU or parallel computing concepts.
  • Awareness of edge or embedded computing constraints such as memory, latency, throughput, and power limitations.
  • Strong analytical, problem-solving, and communication skills.
  • Willingness to learn RF, SAR, and edge-deployed ML methods through mentorship and hands-on work.
  • Are able to obtain an Interim Secret Clearance by your start date and can ultimately obtain a TS/SCI. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information; eligibility requirements include U.S. citizenship.

You'll go above and beyond our minimum requirements if you...
  • Experience with GPU programming, accelerated computing, or performance optimization tools and frameworks.
  • Exposure to deploying software or machine learning models on embedded or edge computing platforms.
  • Familiarity with machine learning frameworks such as PyTorch, TensorFlow, or similar toolkits.
  • Exposure to RF systems, remote sensing, image formation, SAR, or related sensing modalities.
  • Experience with data curation, labeling, preprocessing, or dataset management for machine learning applications.
  • Experience working in Linux-based development environments.

About Us
Why Work at APL?
The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation's most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.
At APL, we celebrate our differences of perspectives and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL's campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at https://www.jhuapl.edu/careers.
All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law. APL is committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact Accessibility@jhuapl.edu.
The referenced pay range is based on JHU APL's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation. Additional compensation may be provided in the form of a sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis.
Minimum Rate
$85,000 Annually
Maximum Rate
$165,000 Annually

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