We are seeking an entry-level engineer or scientist to support the growth of RF/machine learning ... Deep SAR expertise is not required. As a member of our team, you will... * Support development and ...
We are seeking an entry-level engineer or scientist to support the growth of RF/machine learning ... Deep SAR expertise is not required. As a member of our team, you will... * Support development and ...
We are seeking an entry-level engineer or scientist to support the growth of RF/machine learning ... Deep SAR expertise is not required. As a member of our team, you will... * Support development and ...
We are seeking an entry-level engineer or scientist to support the growth of RF/machine learning ... Deep SAR expertise is not required. As a member of our team, you will... * Support development and ...
Entry-Level Controls Service Technician
Owings Mills, MD · On-site
$28.75 - $38/hr
Deep understanding of BAS control components, control strategies, and programming. * Software ... Access to world-class continuous learning opportunities, workshops, and certifications. * Career ...
Entry-Level Controls Service Technician
Owings Mills, MD · On-site
$28.75 - $38/hr
Deep understanding of BAS control components, control strategies, and programming. * Software ... Access to world-class continuous learning opportunities, workshops, and certifications. * Career ...
Front End Entry Level
Westminster, MD · On-site
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Ellicott City, MD · On-site
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Phoenix, MD · On-site
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Phoenix, MD · On-site
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Bethesda, MD · On-site
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Bethesda, MD · On-site
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Annapolis, MD · On-site
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Annapolis, MD · On-site
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Annapolis, MD · On-site
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Entry Level Deep Learning information
See Maryland salary details
$20.4K - $36.4K
24% of jobs
$37.1K is the 25th percentile. Wages below this are outliers.
$36.4K - $52.3K
31% of jobs
$52.3K - $68.3K
8% of jobs
$68.3K - $84.2K
2% of jobs
$84.2K - $100.2K
2% of jobs
$100.2K - $116.1K
3% of jobs
$116.1K - $132.1K
4% of jobs
$134.5K is the 75th percentile. Wages above this are outliers.
$132.1K - $148K
5% of jobs
$148K - $164K
9% of jobs
$164K - $179.9K
8% of jobs
$179.9K - $195.9K
4% of jobs
$20.4K
$88.9K
$195.9K
How much do entry level deep learning jobs pay per year?
As of Aug 11, 2026, the average yearly pay for entry level deep learning in Maryland is $88,881.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,876.00 and $148,017.00 per year, depending on experience, location, and employer.
What is the difference between Entry Level Deep Learning vs Entry Level Machine Learning?
| Aspect | Entry Level Deep Learning | Entry Level Machine Learning |
|---|---|---|
| Required Credentials | Bachelor's in CS, Data Science, or related; familiarity with neural networks | Bachelor's in CS, Data Science, or related; basic understanding of algorithms |
| Work Environment | Research labs, tech companies, AI startups | Tech firms, finance, healthcare, and various industries |
| Employer & Industry Usage | AI-focused roles, research institutions | Broader industry applications, including analytics and automation |
| Common Search & Comparison | Often compared for specialization in neural networks and deep architectures | More general, covers broader ML techniques |
Entry Level Deep Learning focuses on neural networks and complex models, often requiring knowledge of frameworks like TensorFlow or PyTorch. Entry Level Machine Learning covers a wider range of algorithms and techniques. Both roles share foundational skills but differ in specialization and application scope.
What are entry level deep learning jobs?
Entry level deep learning jobs are positions designed for individuals who are new to the field of artificial intelligence and machine learning, typically recent graduates or those with limited professional experience. These roles often involve assisting in building, training, and testing neural network models, as well as preprocessing data and supporting senior data scientists or machine learning engineers. Entry level positions may also include tasks such as researching recent advancements, implementing standard algorithms, and contributing to team projects under supervision. A strong foundation in Python, deep learning frameworks like TensorFlow or PyTorch, and an understanding of basic machine learning concepts are usually required.
What are some common challenges faced by entry level deep learning professionals, and how can they be addressed?
Entry-level deep learning professionals often encounter challenges such as understanding complex architectures, managing large datasets, and optimizing model performance. Navigating unfamiliar frameworks and debugging code can also be daunting at first. These challenges can be addressed by seeking mentorship from experienced colleagues, participating in code reviews, and dedicating time to hands-on projects. Additionally, staying updated with the latest research and utilizing online communities or forums can provide valuable support and resources.
What are the key skills and qualifications needed to thrive as an entry level deep learning professional?
To thrive as an Entry Level Deep Learning professional, you need a solid understanding of machine learning fundamentals, mathematics (especially linear algebra and calculus), and proficiency in programming languages such as Python. Experience with frameworks like TensorFlow or PyTorch and familiarity with version control systems like Git are typically required. Strong problem-solving abilities, eagerness to learn, and the ability to work collaboratively set candidates apart in this field. These skills and qualities are essential for building, troubleshooting, and improving deep learning models in a rapidly evolving technical landscape.
What are the most commonly searched types of Deep Learning jobs in Maryland? The most popular types of Deep Learning jobs in Maryland are:
What are popular job titles related to Entry Level Deep Learning jobs in Maryland? For Entry Level Deep Learning jobs in Maryland, the most frequently searched job titles are:
What job categories do people searching Entry Level Deep Learning jobs in Maryland look for? The top searched job categories for Entry Level Deep Learning jobs in Maryland are:
- Online Assistant Professor Of Biochemistry
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- Assistant Professor History
- Senior Specialist Violin Professor
- Live In Clarinet Professor
- Assistant Professor Of Strategic Management
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2026 Graduate - Synthetic Aperture Radar ML Engineer - Imaging Systems
Laurel, MD • On-site
Full-time
Medical, Dental, Vision, Life, Retirement, PTO
Re-posted 9 hours ago
Johns Hopkins Applied Physics Laboratory rating
9.6
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...
Qualifications
You meet our minimum qualifications if you have...
You'll go above and beyond our minimum requirements if you...
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
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
What Johns Hopkins Applied Physics Laboratory employees say
Pay
Hours and flexibility
Workplace
Get the full story on Breakroom
About Johns Hopkins Applied Physics Laboratory
Sourced by ZipRecruiter
Industry
Manufacturing
Company size
5,001 - 10,000 Employees
Headquarters location
Laurel, MA, US