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Scientific Machine Learning Jobs in Maryland (NOW HIRING)

PassFort

Machine Learning Engineer

Berlin, MD · On-site

$79.93 - $137.02/hr

Master's or PhD in Computer Science, Robotics, Electrical Engineering, or a related field ... Solid understanding of machine learning, deep learning, and autonomous systems. Preferred Skills:

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Scientific Machine Learning information

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 Maryland?

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

What job categories do people searching Scientific Machine Learning jobs in Maryland look for?

The top searched job categories for Scientific Machine Learning jobs in Maryland are:

What cities in Maryland are hiring for Scientific Machine Learning jobs?

Cities in Maryland with the most Scientific Machine Learning job openings:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine 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.

Data Scientist & Machine Learning Engineer Intern

DMS International

Silver Spring, MD • On-site, Remote

Part-time, Internship

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Data Management Services, Inc. (DMS International) is a professional services firm headquartered in Silver Spring, Maryland, with work locations throughout the continental United States. We prepare managers and executives to lead their workforce through customized learning solutions that drive the standards of an ever-changing world. We build creative, unique, and engaging learning experiences for commercial, civilian and defense organizations. Our high-caliber talent, delivery methodology and innovative solutions contribute to preparing a workforce that is ready for the future. You can join us on this journey to bring efficiency and creativity to our customers.
At DMS, we are the catalyst for effective workforce transformation. To achieve this, we hire professionals who take pride in doing quality work and who are excited about contributing to the professional development of tomorrow's leaders.
DMS seeks candidates that possess and display the attributes that reflect our Core Values of:
  • Quality in delivering solutions
  • Leadership
  • Teamwork
  • Innovation
  • Integrity in conduct
  • Responsiveness to our customer's mission.

DMS International is an Equal Opportunity Employer. We make employment decisions without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, pregnancy, childbirth, lactation and related medical conditions, genetic factors, military/veteran status, or other characteristics protected by law. We encourage individuals from all backgrounds to apply.
Job Description
DMS is seeking a Data Scientist & Machine Learning Engineer Intern to join our technical team. The intern will support the design, development, testing, and implementation of AI-powered products for content creation, learning, training, simulations, and decision support. Working under the supervision of the AI and Simulation Program Manager, the intern will collaborate with developers, instructional designers, simulation specialists, and subject matter experts to transform data and emerging AI technologies into practical applications.
Responsibilities
  • Support the development of Generative AI and Large Language Model (LLM) applications, including prompt engineering and Retrieval-Augmented Generation (RAG)
  • Develop AI capabilities for transforming source documents into courses, learning content, assessments, scenarios, case studies, and other digital content
  • Assist in developing AI-powered simulations and serious games, including dynamic scenarios, intelligent agents, participant analytics, and after-action reports
  • Collect, clean, analyze, and visualize structured and unstructured data
  • Develop natural language processing (NLP) solutions for document summarization, semantic search, classification, information extraction, and question answering
  • Build prototypes and integrate AI/ML models with applications through APIs and cloud services
  • Conduct model testing and evaluation for performance, accuracy, reliability, bias, and hallucinations
  • Support responsible AI practices, model documentation, data governance, and AI risk management
  • Develop, train, test, and evaluate machine learning and predictive models
  • Research emerging technologies such as agentic AI, multimodal AI, synthetic data, digital twins, knowledge graphs, and adaptive learning

Required Skills & Experience
  • Familiarity with machine learning frameworks such as Scikit-learn, PyTorch, and/or TensorFlow
  • Knowledge of Generative AI concepts, LLMs, prompt engineering, embeddings, RAG, and/or Hugging Face
  • Familiarity with REST APIs, Git/GitHub, and basic application development
  • Knowledge of statistical analysis, data visualization, and predictive modeling
  • Strong analytical and problem-solving skills
  • Curiosity about emerging AI technologies and willingness to experiment and learn
  • Ability to work independently and collaboratively within a multidisciplinary team
  • Experience through academic projects, research, hackathons, personal projects, or internships involving machine learning, Generative AI, NLP, simulations, analytics, or AI application development is preferred
  • GitHub portfolio or examples of AI/ML projects are encouraged
  • Experience or coursework in Python, SQL, Pandas, NumPy, and Jupyter Notebook
  • Exposure to OpenAI, Azure OpenAI, IBM watsonx, AWS/GCP AI services, LangChain, LlamaIndex, vector databases, FastAPI, Django, Flask, or Docker is a plus.

Education
  • Currently pursuing or recently completed a Bachelor's, Master's, or doctoral degree in Computer Science, Data Science, Artificial Intelligence/Machine Learning, Statistics, Applied Mathematics, Computer or Software Engineering, Information Systems, Operations Research, or a related quantitative or technical field

Position Type
  • Part-time Intern

Location
  • Remote

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