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Scientific Machine Learning Jobs in Baltimore, MD

asrcfh

Junior Data Scientist

Greenbelt, MD · On-site

Develop, implement, and optimize machine learning and deep learning models for scientific and real-world applications, including vision-language systems and multimodal architectures. * Construct and ...

asrcfh

Junior Data Scientist

Greenbelt, MD · On-site

Develop, implement, and optimize machine learning and deep learning models for scientific and real-world applications, including vision-language systems and multimodal architectures. * Construct and ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Baltimore, MD

Scientific Machine Learning information

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$13

$31

$52

How much do scientific machine learning jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for scientific machine learning in Baltimore, MD is $31.28, according to ZipRecruiter salary data. Most workers in this role earn between $19.09 and $39.90 per hour, depending on experience, location, and employer.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Baltimore, MD?

For Scientific Machine Learning jobs in Baltimore, MD, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in Baltimore, MD look for?

The top searched job categories for Scientific Machine Learning jobs in Baltimore, MD are:

What cities near Baltimore, MD are hiring for Scientific Machine Learning jobs?

Cities near Baltimore, MD with the most Scientific Machine Learning job openings:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Baltimore, MD as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $65,056 per year, or $31.3 per hour.

Artificial Intelligence Machine Learning Engineer 2

Captivation Software

Annapolis Junction, MD • On-site

$61.25 - $81/hr

Full-time

Re-posted 17 days ago

Job description

Description

Captivation Software is looking for a mid level AI/ML engineer who will be responsible for designing, creating, testing, and productizing AI/ML algorithms to solve business challenges

Responsibilities
  • Select appropriate data sets
  • Perform statistical analysis
  • Run machine learning algorithms
  • Use results to improve models
  • Train and retrain systems when needed
  • Experience in working with various ML libraries and packages
  • Run standard test and evaluation protocols
  • Provide system integration oversight
  • Oversee Test and evaluation of AI and ML algorithms through an iterative design process to meet verification and validation requirements
  • Research and implement a broad range of AI and ML algorithms and tools
  • Design or Select appropriate data and knowledge representation methods
  • Recognize software architecture, data modelling, and data structures
  • Transform and convert data science prototypes into scalable solutions
  • Verify data and model output quality
  • Identify differences in data distribution that affect model performance
Requirements
Security Clearance:
  • Must currently hold a Top Secret/SCI U.S. Government security clearance with a favorable Polygraph, therefore all candidates must be a U.S. citizen
Minimum Qualifications:
  • Five (5) years of experience deploying machine learning algorithms is required.
  • A Master's or Ph.D. degree in advanced math, artificial intelligence, data science, computer science or deep learning from an accredited college or university is required.
  • 5 additional years machine learning experience with a relevant Bachelor's degree may be substituted for a Master's degree.
Required Skills:
  • Demonstrated abilities in software engineering and AI/ML model test and evaluation.

This position is open for direct hires only. We will not consider candidates from third party staffing/recruiting firms.

Apply