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Entry Level Deep Learning Jobs in Maryland (NOW HIRING)

... Applying deep learning techniques and neural networks to improve predictive analytics ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

CompTIA A+ Tutor

Rockville, MD · Remote

$25 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of CompTIA A+ examination content covering mobile devices, networking, hardware ...

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Entry Level Deep Learning information

See Maryland salary details

$20.4K

$88.9K

$195.9K

How much do entry level deep learning jobs pay per year?

As of Sep 1, 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 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 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 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 is the difference between Entry Level Deep Learning vs Entry Level Machine Learning?

AspectEntry Level Deep LearningEntry Level Machine Learning
Required CredentialsBachelor's in CS, Data Science, or related; familiarity with neural networksBachelor's in CS, Data Science, or related; basic understanding of algorithms
Work EnvironmentResearch labs, tech companies, AI startupsTech firms, finance, healthcare, and various industries
Employer & Industry UsageAI-focused roles, research institutionsBroader industry applications, including analytics and automation
Common Search & ComparisonOften compared for specialization in neural networks and deep architecturesMore 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 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:

Infographic showing various Entry Level Deep Learning job openings in Maryland as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $88,881 per year, or $42.7 per hour.

Anesthesiology Faculty - Data Science Research

University of Maryland, Baltimore

Baltimore, MD • On-site

$69K - $164K/yr

Full-time

Medical, PTO

Re-posted 25 days ago


University Of Maryland, Baltimore rating

7.7

Company rating: 7.7 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

262nd of 627 rated colleges and universities


Job description

Job Description
We are seeking an entry-level data scientist, junior faculty to join our clinical data research lab. The ideal candidate will have a strong foundation in statistics, machine learning, and data programming. This position is expected to work in two separate locations, in the STAR-ORC lab located at the UMB campus and at the new University of Maryland-Institute for Health Computing, which is a major computational research hub in North Bethesda that uses next-generation computational analytics to improve health and human disease. The position will be responsible for developing and implementing data analysis pipelines to support a variety of clinical research projects, as well as mathematical modeling to improve predictions and analytic capabilities that merge different kinds of data assets (i.e., clinical, biological, environmental).
Job Duties:
l Lead the data analysis in clinical and laboratory research projects. Join team meetings and provide suggestions in research methodologies and plannings.
l Develop grants applications.
l Develop and maintain data analysis pipelines, including data extraction, cleaning, transformation, quality assurance, pipeline monitoring and maintenance.
l Apply statistical and machine learning methods to support meaningful data analyses.
l Create high-quality and informative graphs and write corresponding manuscript sections to describe the methodology and results in detail for scientific publications.
l Work with other members of the team to design and conduct clinical research studies.
l Collaborate with clinicians and scientists to translate research findings into clinical practice.
l Apply next-generation computational approaches to clinical, biological, and environmental big data assets.
l Integrate high-level mathematics to predict events that are important in health outcomes, including treatment response, hospitalizations, and other end-points.
l Promote analytics that consider bias and improve health equity.
Required Qualifications:
l Strong programming skills in Python, R, or another statistical programming languages.
l Experience with statistical methods (such as descriptive statistics, hypothesis testing, time series analysis, etc.) and machine learning methods (data cleaning, feature engineering, hyperparameter tuning, model evaluation and interpretation).
l Scientific literature search and review skills.
l Excellent analytical and problem-solving skills. Be able to work independently and collaboratively.
l Good communication (written and oral) and interpersonal skills.
l Experience as a good team member or team leader.
Preferred Qualifications:
l Experience with clinical data and clinical research methods.
l Experience with statistical and machine learning libraries and tools, such as Scikit-learn, pandas.
l Experience as a good team member or team leader, autonomy in the health care system clinical analytics field, and pursuing health equity.
l A significant publication record in clinical/health care analytics or healthcare.
l A track record of applications for grant funding in clinical/health care analytics.
l Experience with deep learning and its framework (e.g. Pytorch) is a plus.
Required Education and Experience:
l Doctoral degree in statistics, computer science, data science, or a related field.
l A faculty member at an academic medical center (or equivalent) in good standing at the level of assistant professor or above (rising assistant professors also considered).
l 0-2 years of experience in a data science role.
UMB is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law or policy. If you need a reasonable accommodation for a disability for any part of the employment process, please submit an online or contact . Please note that only inquiries concerning a request for reasonable accommodation will be responded to from this email address.
Qualifications
Please reference this recruitment advertisement and position number in your cover letter. Interested candidates should use this online portal to submit their cover letter, CV and contact information for three references.
Qualified applicants must have a doctoral degree, professional experience consistent with the faculty rank of Assistant Professor or higher and a track record of independent research funding from diverse sources.
Salary Range - Base Compensation [Research Faculty w/ PhD Degree]
Expected Salary Range: $69,336 to $164,684.
*The referenced salary range reflects base pay, which is based on faculty rank and years in rank. This salary range does not include all components of the Department of Anesthesiology faculty compensation program or pay from participation in Department of Anesthesiology incentive compensation programs. Therefore, the actual compensation paid to the selected candidate may vary from the salary range stated herein. For more information, please contact the hiring department.
The referenced salary range represents the minimum and maximum salaries for this position and is based on the University of Maryland School of Medicine's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.
UMB offers a comprehensive that prioritizes wellness, work/life balance, and professional development. This position participates in a retirement program that must be selected and is effective on your date of hire. Faculty receive a generous leave package that includes over 4 weeks of vacation accrued each year, paid holidays, personal leave, unlimited accrual of sick time, and comprehensive health insurance; professional learning and development programs; tuition remission for employees and their dependents at any University System of Maryland school.
Qualifications
Please reference this recruitment advertisement and position number in your cover letter. Interested candidates should use this online portal to submit their cover letter, CV and contact information for three references.
Qualified applicants must have a doctoral degree, professional experience consistent with the faculty rank of Assistant Professor or higher. Expected rank for this position will be Assistant Professor or higher, however, final rank and tenure status will be commensurate with selected candidate's experience

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