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Remote Deep Learning Jobs in Maryland (NOW HIRING)

Umd

Post-Doctoral Associate

College Park, MD · On-site +1

$85K - $95K/yr

Develop and improve machine learning and deep learning models for crop yield forecasting and ... Ph.D. in remote sensing, geospatial science, agricultural engineering, computer science ...

Metric5

AI Learning Specialist

Windsor Mill, MD · Remote

$150K - $170K/yr

We are looking for an AI Learning Specialist who combines deep technical knowledge with a talent ... Remote within the United States (monthly travel to Baltimore, MD may be required) Clearance: Must ...

Hewlett Packard Enterprise Development LP

AI Solution Engineer This role has been designated as 'Remote/Teleworker', which means you will ... Understanding of hardware requirements associated with deep learning model training or inference ...

Hewlett Packard Enterprise Development LP

AI Solution Engineer This role has been designated as 'Remote/Teleworker', which means you will ... Understanding of hardware requirements associated with deep learning model training or inference ...

Hewlett Packard Enterprise

AI Solution Engineer This role has been designated as 'Remote/Teleworker', which means you will ... Understanding of hardware requirements associated with deep learning model training or inference ...

NinjaOne

Senior Data Software Engineer

Baltimore, MD · On-site +1

$121.70K - $160.50K/yr

Location - We are flexible on remote working from home, if you are located in the USA and reside in ... and Deep Learning frameworks. About Us NinjaOne automates the hardest parts of IT to deliver ...

NinjaOne

Senior Data Software Engineer

Baltimore, MD · On-site +1

$121.70K - $160.50K/yr

Location - We are flexible on remote working from home, if you are located in the USA and reside in ... and Deep Learning frameworks. About Us NinjaOne automates the hardest parts of IT to deliver ...

Cloudera

$150K - $180K/yr

Data Science and ML experience - (R, Python, Deep Learning Frameworks etc.) * Integration Products ... Employee Resource Groups EEO/VEVRAA #LI-MH2 #LI-remote

Autodesk

US or Canada Remote Responsibilities * Lead architecture and delivery for major ML platform ... Deep experience in software architecture, distributed systems, large-scale data platforms, or ML ...

Hewlett Packard Enterprise

$119.50K/yr

Lead Delivery Solution Architect This role has been designated as 'Remote/Teleworker', which means ... Expertise with Machine Learning and deep learning * Data Science knowledge and experience * Big ...

Hewlett Packard Enterprise Development LP

$119.50K/yr

Lead Delivery Solution Architect This role has been designated as 'Remote/Teleworker', which means ... Expertise with Machine Learning and deep learning * Data Science knowledge and experience * Big ...

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All JobsRemote Deep Learning JobsRemote Deep Learning Jobs in Maryland

Remote Deep Learning information

See Maryland salary details

$21.4K

$130.6K

$213.3K

How much do remote deep learning jobs pay per year?

As of May 28, 2026, the average yearly pay for remote deep learning in Maryland is $130,570.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,717.00 and $168,948.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Deep Learning Engineer, and why are they important?

To thrive as a Remote Deep Learning Engineer, you need strong programming skills in Python, a deep understanding of machine learning algorithms, and typically a degree in computer science, engineering, or a related field. Proficiency with frameworks like TensorFlow or PyTorch, as well as cloud computing platforms such as AWS or Google Cloud, is essential, and certifications in these technologies can be advantageous. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These skills ensure effective development, deployment, and maintenance of deep learning models while working independently in distributed teams.

What are some common challenges faced by remote deep learning engineers, and how can they be addressed?

Remote deep learning engineers often encounter challenges such as limited access to high-performance computing resources, communication barriers with distributed teams, and difficulties in collaborating on large codebases or datasets. These issues can be mitigated by leveraging cloud-based platforms for scalable computing, using clear communication tools like Slack or Zoom for regular check-ins, and employing version control systems like Git for collaborative code management. Proactively setting up workflows and documentation helps ensure smooth collaboration and project continuity within a remote environment.

What is a Remote Deep Learning job?

A Remote Deep Learning job involves working with artificial intelligence and machine learning models, particularly using deep neural networks, from a location outside a traditional office, often from home. Professionals in this field design, build, and optimize algorithms that enable computers to learn from large amounts of data. They often work on projects such as image and speech recognition, natural language processing, or autonomous systems. The remote aspect allows flexibility and access to global opportunities, but requires strong communication skills and the ability to collaborate virtually with teams.

What is the difference between Remote Deep Learning vs Remote Machine Learning Engineer?

AspectRemote Deep LearningRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with neural networksBachelor's/Master's in CS, Data Science, or related; experience with algorithms and data modeling
Work EnvironmentCollaborative teams, research-focused, often in tech or AI companiesDevelopment teams, data-driven projects, across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech companies, finance, healthcare, e-commerce

Remote Deep Learning specialists focus on designing and training neural networks for AI applications, often requiring advanced knowledge of deep neural architectures. Remote Machine Learning Engineers work on developing algorithms and models for broader data analysis and predictive tasks. While both roles involve machine learning, deep learning emphasizes neural networks, whereas machine learning engineers may work with a variety of algorithms across industries.

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 Remote Deep Learning jobs in Maryland? For Remote Deep Learning jobs in Maryland, the most frequently searched job titles are:
What job categories do people searching Remote Deep Learning jobs in Maryland look for? The top searched job categories for Remote Deep Learning jobs in Maryland are:
What cities in Maryland are hiring for Remote Deep Learning jobs? Cities in Maryland with the most Remote Deep Learning job openings:
Remote Deep Learning jobs near you

Post-Doctoral Associate

Umd

College Park, MD • On-site, Remote

$85K - $95K/yr

Full-time

Posted 13 days ago

Job description

Job Description SummaryPOSITION SUMMARY:
The Department of Geographical Sciences at the University of Maryland, College Park, in partnership with NASA Harvest, is seeking a Postdoctoral Associate to contribute to research at The intersection of satellite remote sensing, crop modeling, machine learning, and food security.
The position is housed within the yield modeling group at NASA Harvest and will support projects focused on agricultural monitoring, crop yield forecasting, and the development of scalable, AI-enabled geospatial data systems for Sub-Saharan Africa and other food-insecure regions.
POSITION OVERVIEW:
The successful candidate will work under the supervision of Dr. Ritvik Sahajpal and collaborate with an international network of partners, including FAO, Microsoft AI for Good, GEOGLAM, and other NASA Harvest Consortium members. The role offers an opportunity to contribute to high-impact, operational systems that directly support national governments, international organizations, and development partners in making evidence-based agricultural and food security decisions.
Develop and improve machine learning and deep learning models for crop yield
forecasting and agricultural monitoring at subnational to national scales.
Integrate process-based crop simulation models (e.g., EPIC, DSSAT, APSIM) with data-driven approaches, including knowledge-guided machine learning (KGML)
frameworks.
Process, analyze, and extract features from multi-source satellite remote sensing data (optical, SAR, thermal) using cloud computing platforms such as Google Earth Engine.
Contribute to the design and implementation of scalable, operational geospatial data pipelines for agricultural information systems.
Collaborate with international partners to validate models against ground truth and official agricultural statistics across multiple countries.
Publish findings in peer-reviewed journals and present results at scientific conferences and to stakeholders in government and international organizations.
Mentor and support graduate and undergraduate research assistants as needed.
Support and deliver training at workshops for partners, stakeholders, and
capacity-building events.
MINIMUM QUALIFICATIONS:
Ph.D. in remote sensing, geospatial science, agricultural engineering, computer science, environmental science, or a closely related field.
Strong programming skills in Python, with demonstrated experience building scientific computing workflows and data pipelines.
Demonstrated expertise in machine learning or deep learning applied to geospatial or agricultural problems (e.g., crop classification, yield prediction, anomaly detection).
PREFERRED QUALIFICATIONS:
Experience with or strong interest in process-based crop simulation models and their integration with ML/AI approaches.
Ability to work with large geospatial datasets and cloud computing platforms (Google Earth Engine, or similar).
Strong written and oral communication skills, including experience with scientific publications.
Ability to work independently and collaboratively within a multidisciplinary, international research team.
Experience with satellite remote sensing data processing and analysis (e.g. Sentinel-2, Landsat, MODIS/VIIRS, SAR).
LICENSES/ CERTIFICATIONS:
N/A
PHYSICAL DEMANDS:
N/AAdditional Job Details

Required Application Materials:

1. A cover letter describing research interests, relevant experience, and how your skills complement the position requirements.

2. A current curriculum vitae (CV) including a list of publications.

3. Contact information for three professional references (references will only be contacted if you are shortlisted for an interview).

Applications should be submitted via the University of Maryland eTerp system. Review of applications will begin immediately and continue until the position is filled. For questions, please contact Dr. Ritvik Sahajpal at ritvik@umd.edu.

Best Consideration Date: May 22, 2026

Open Until Filled: Yes

Salary Range: $85,000 - $95,000

Commensurate with experience

Financial Disclosure RequiredNo

For more information on Financial Disclosure, please visit Maryland's State Ethics Commission website.

DepartmentBSOS-GeographyWorker Sub-Type Faculty RegularSalary Range$85,000 - $95,000
Benefits Summary

For more information on Regular Faculty benefits, select this link.

Background Checks

Offers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify anyone from employment. Before any adverse decision, the finalist will have an opportunity to provide information to the University regardingdisclosablebackground checkinformation. The University reserves the right to rescind the offer of employment or otherwise decline or terminate employment if the information reported by the background check is deemed incompatible with the position, regardless of when the background check is completed.

Employment Eligibility

The successful candidate must complete employment eligibility verification (on Form I-9) by presenting documents that establish identity and work authorization within the timeframe required by federal immigration law, and where applicable, to demonstrate renewed employment authorization. Failure to complete employment eligibility verification or reverification within the timeframe set forth by law may result in suspension or termination of employment.

EEO Statement

The University of Maryland, College Park is an Equal Opportunity Employer. All qualified applicants will receive equal consideration for employment. Please read the University's Equal Employment Opportunity Statement of Policy.

Title IX Non-Discrimination NoticeResources

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