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Entry Level Machine Learning Jobs in Baltimore, MD

XPERTECHS

Automation Associate

Columbia, MD · On-site

Description This role is an entry level position aimed at a blend of AI-focused project work ... Support AI-related projects including data analysis, automation solutions, machine learning ...

SynergisticIT

Entry Level UI Developer

Annapolis, MD · On-site

Excellent written and verbal communication skills For Data Science/Machine Learning Required Skills ... entry-level position each additional Technical skill helps a candidate's resume to be picked by ...

SynergisticIT

UI Developer

Silver Spring, MD · On-site

$51.75 - $67.25/hr

Currently, we are looking for qualified entry-level Data Scientists who can apply Data Science ... If you're lured by the endless possibilities presented by AI, Machine Learning, IoT, and Data ...

84 Lumber Company

Entry-Level Manager Trainee

MD · On-site

$45K - $50K/yr

Manager Trainees must complete the learning plan and course of study as outlined within the ... You may also work around machinery and airborne particles. Responsibilities * Payroll, Invoicing ...

84 Lumber Company

Entry Level Manager Trainee

MD · On-site

$46K - $49K/yr

Manager Trainees must complete the learning plan and course of study as outlined within the ... You may also work around machinery and airborne particles. Responsibilities * Payroll, Invoicing ...

Metova Federal

AI Intern

Hanover, MD

Experience with responsive software development and design principles. * Entry level understanding ... Familiarity with machine learning or data science concepts and experience with data visualization ...

Metova Federal

AI Intern

Hanover, MD · On-site

Experience with responsive software development and design principles. * Entry level understanding ... Familiarity with machine learning or data science concepts and experience with data visualization ...

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All JobsEntry Level Machine Learning JobsEntry Level Machine Learning Jobs in Baltimore, MD

Entry Level Machine Learning information

See Baltimore, MD salary details

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How much do entry level machine learning jobs pay per hour?

As of Jun 24, 2026, the average hourly pay for entry level machine learning in Baltimore, MD is $17.35, according to ZipRecruiter salary data. Most workers in this role earn between $15.53 and $18.85 per hour, depending on experience, location, and employer.

What types of projects can an entry-level machine learning professional expect to work on in their first year?

As an entry-level machine learning professional, you’ll typically start by supporting more senior data scientists and engineers with tasks such as data cleaning, exploratory data analysis, and building baseline models. You may work on pilot projects like developing recommendation systems, automating simple classification tasks, or contributing to model evaluation and performance tuning. Collaboration with cross-functional teams—including software engineers, product managers, and domain experts—is common, providing valuable exposure to real-world business problems and laying a foundation for more complex responsibilities as you gain experience.

What is a $900,000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers, AI research directors, or chief AI officers, often found in large tech companies or specialized firms. These positions usually require extensive experience, advanced skills in deep learning, data science, and proficiency with tools like TensorFlow or PyTorch, along with leadership responsibilities and sometimes equity or bonuses. Such salaries are rare and generally reflect seniority, expertise, and the strategic importance of AI initiatives within organizations.

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

To thrive as an Entry Level Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially in Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems like Git, and data analysis libraries is commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help differentiate candidates in collaborative and fast-evolving environments. These skills and qualifications are essential for building, testing, and improving machine learning models that drive innovation and business value.

What is the difference between Entry Level Machine Learning vs Data Analyst?

AspectEntry Level Machine LearningData Analyst
Required CredentialsBachelor's in CS, Math, or related; some knowledge of programming and statisticsBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, startups, research labs; focus on developing models and algorithmsBusiness, finance, marketing; focus on interpreting data and generating reports
Employer & Industry UsageTech, e-commerce, healthcare; roles involve building predictive modelsRetail, finance, consulting; roles involve analyzing data trends and insights

Entry Level Machine Learning roles focus on developing algorithms and models using programming and statistical skills, often in tech-driven environments. Data Analysts interpret and visualize data to support business decisions, typically using tools like Excel and SQL. While both roles require analytical skills, Machine Learning positions emphasize coding and model development, whereas Data Analysts focus on data interpretation and reporting.

Which 3 jobs will survive AI?

Entry level machine learning roles are likely to persist as they require specialized skills in data analysis, programming, and understanding complex algorithms. Jobs that involve creative thinking, emotional intelligence, or physical tasks, such as data scientists, AI specialists, and software engineers, are expected to remain in demand despite AI advancements.

How to get into machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, mathematics, and data analysis. Gaining skills through online courses, tutorials, and practicing with projects using tools like Python and libraries such as scikit-learn or TensorFlow can help build a portfolio. Earning certifications or completing relevant coursework can also improve job prospects for beginners.

What are entry level machine learning jobs?

Entry level machine learning jobs are positions designed for individuals just starting their careers in the field of machine learning. These roles typically involve working on data preparation, building and testing basic models, and assisting senior data scientists or engineers. Common job titles include Machine Learning Engineer, Data Analyst, or Junior Data Scientist. Requirements often include proficiency in programming languages such as Python, foundational knowledge of statistics, and experience with machine learning libraries. These jobs provide hands-on experience and mentorship to help new professionals grow their skills.

What Are Entry-Level Machine Learning Jobs?

Entry-level machine learning jobs focus on creating and using software for the development of artificial intelligence (AI). In this role, you may help program computer software, engineer mechanical solutions, help develop learning objectives, and use analytics to determine whether or not the technology created is meeting development goals. Many entry-level machine learning jobs focus on particular parts of the industry. For example, some companies focus on surveillance and intelligence, while others are creating technology for self-driving vehicles. Employers often use this position as a type of extended learning period to help you develop your skills before you start taking responsibility for major projects.

What engineers make $500,000?

Senior engineers in fields like software, electrical, or aerospace engineering can reach or exceed $500,000 annually, especially with experience, specialized skills, and leadership roles. High-paying positions often require advanced expertise, certifications, and work in competitive industries or companies with lucrative compensation packages.
More about Entry Level Machine Learning jobs
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Entry Level Machine Learning jobs near you
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 12 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 57 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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