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Scientific Machine Learning Jobs in Chester, VA (NOW HIRING)

WorkNovas LLC

Machine Learning Engineer

Richmond, VA · On-site

... Science, Engineering, or a related field 5+ years of experience in machine learning, AI engineering, or applied ML Strong proficiency in Python for ML and backend development Hands-on experience ...

Varsity Tutors

Machine Learning Tutor

Richmond, VA · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Chester, VA

Scientific Machine Learning information

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$12

$28

$48

How much do scientific machine learning jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for scientific machine learning in Chester, VA is $28.97, according to ZipRecruiter salary data. Most workers in this role earn between $17.69 and $36.92 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 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 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 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 cities near Chester, VA are hiring for Scientific Machine Learning jobs? Cities near Chester, VA with the most Scientific Machine Learning job openings:
Scientific Machine Learning jobs near you
Machine Learning with Python Development

Machine Learning with Python Development

Palnar

Richmond, VA • On-site

$49.75 - $68.75/hr

Full-time

Re-posted 10 days ago

Job description

Summary:
Good Machine Learning foundations, practical experience with classification, regression and clustering methods
strong python coding, computing fundamentals/data structures, SQL, experience with Hadoop stack
Exposure/experience in NLP is preferable, experience with Deep Learning methods is preferable
Education: Requires bachelor's degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent degree

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