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Entry Level Applied Mathematics Jobs in Washington

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Entry Level Applied Mathematics information

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$25.5K

$66.6K

$107K

How much do entry level applied mathematics jobs pay per year?

As of Aug 7, 2026, the average yearly pay for entry level applied mathematics in Washington is $66,639.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,000.00 and $79,300.00 per year, depending on experience, location, and employer.

What is an entry level applied mathematics job?

An Entry Level Applied Mathematics job involves using mathematical theories, computational techniques, and data analysis to solve real-world problems in industries like finance, engineering, technology, and healthcare. Responsibilities may include statistical modeling, algorithm development, and data interpretation. These roles often require proficiency in programming languages such as Python or MATLAB and strong analytical skills. Employers typically seek candidates with a bachelor's degree in mathematics, applied mathematics, or a related field. This job serves as a foundation for more specialized or advanced roles in data science, actuarial science, or operations research.

What are the key skills and qualifications needed to thrive in the entry level applied mathematics position, and why are they important?

Success in an Entry Level Applied Mathematics role requires a strong grasp of mathematical concepts, analytical thinking, and a bachelor's degree in mathematics, statistics, engineering, or a related field. Proficiency in data analysis tools such as Excel, MATLAB, R, or Python, and familiarity with statistical or mathematical modeling software is commonly expected. Strong problem-solving abilities, communication skills, and teamwork help individuals stand out in this collaborative field. These skills enable accurate analysis, effective communication of findings, and meaningful contributions to solving real-world problems within an organization.

What types of projects or tasks can I expect to work on as an entry level applied mathematics professional?

As an entry level applied mathematics professional, you can expect to work on a variety of tasks including analyzing datasets, building mathematical models to solve business or engineering problems, and supporting research or operational teams with quantitative insights. You may be involved in projects such as forecasting trends, optimizing processes, or assisting in the development of simulation tools. Collaboration with other analysts, engineers, or business units is common and offers valuable exposure to cross-functional teamwork. These responsibilities provide a strong foundation for further growth in fields like data science, operations research, or actuarial science.

What are popular job titles related to Entry Level Applied Mathematics jobs in Washington? For Entry Level Applied Mathematics jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Entry Level Applied Mathematics jobs in Washington look for? The top searched job categories for Entry Level Applied Mathematics jobs in Washington are:
What cities in Washington are hiring for Entry Level Applied Mathematics jobs? Cities in Washington with the most Entry Level Applied Mathematics job openings:
Entry Level Applied Mathematics jobs near you
Infographic showing various Entry Level Applied Mathematics job openings in Washington as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $66,639 per year, or $32 per hour.

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

Re-posted 26 days ago

Johns Hopkins Applied Physics Laboratory rating

9.6

Company rating: 9.6 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

2nd of 73 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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