1

Scientific Machine Learning Jobs in Raleigh, NC (NOW HIRING)

S. or Ph.D in engineering, math, computer science, or related field • Excellent technical ... CoVar is a leader in machine learning and artificial intelligence solutions. Founded in 2011, the ...

As a Machine Learning Engineer, you will help build and operate production systems that power fraud ... You'll work closely with data scientists and engineers to bring models into production, ensuring ...

The Machine Learning Engineer will develop software and machine learning algorithms to address real ... S. or Ph.D in engineering, math, computer science, or related field • Excellent technical ...

Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC ... S. or Ph.D in engineering, math, computer science, or related field * Excellent technical ...

Sr. Machine Learning Engineer Duration: 12 -24 Months Location: Merrimack, NH/ Smithfield, RI ... Engineering, Computer Science, etc.) * 8+ years of proven experience in implementing Big data ...

Machine Learning Engineer

Raleigh, NC · On-site

$96K - $137K/yr

Bachelor's degree or higher in Computer Science, Computer Engineering or a related field required ... Experience with industry-standard machine learning frameworks (PyTorch, TensorFlow, Scikit-Learn ...

Bachelor's degree or higher in Computer Science, Computer Engineering or a related field required ... Experience with industry-standard machine learning frameworks (PyTorch, TensorFlow, Scikit-Learn ...

Bachelor's degree or higher in Computer Science, Computer Engineering or a related field required ... Experience with industry-standard machine learning frameworks (PyTorch, TensorFlow, Scikit-Learn ...

Machine Learning Engineer

Raleigh, NC · On-site

$96K - $137K/yr

Bachelor's degree or higher in Computer Science, Computer Engineering or a related field required ... Experience with industry-standard machine learning frameworks (PyTorch, TensorFlow, Scikit-Learn ...

As a Machine Learning Engineer, you will help build and operate production systems that power our ... You'll work closely with data scientists and engineers to bring models into production ensuring ...

... 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 ...

... 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 ...

... 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 ...

Machine Learning Compiler

Raleigh, NC · On-site

$160K - $240K/yr

Engineering Group, Engineering Group > Machine Learning Engineering General Summary: Lead a team of ... Bachelor's degree in Computer Science, Electrical Engineering, or related field and 10+ years of ...

Engineering Group, Engineering Group > Machine Learning Engineering General Summary: Lead a team of ... Bachelor's degree in Computer Science, Electrical Engineering, or related field and 10+ years of ...

Job Summary : Qualcomm Technologies, Inc. is focused on advancing machine learning compiler ... Required : • Bachelor's degree in Computer Science, Electrical Engineering, or related field and ...

next page

Showing results 1-20

Scientific Machine Learning information

See Raleigh, NC salary details

$13

$30

$50

How much do scientific machine learning jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for scientific machine learning in Raleigh, NC is $30.60, according to ZipRecruiter salary data. Most workers in this role earn between $18.70 and $39.04 per hour, depending on experience, location, and employer.

Is ML a high paying job?

Scientific Machine Learning roles typically offer high salaries due to the specialized skills required, such as expertise in deep learning, data analysis, and programming with tools like Python and TensorFlow. Compensation varies by industry, experience, and location but generally exceeds average tech salaries for comparable roles.

Which 3 jobs will survive AI?

Scientific Machine Learning professionals will likely continue to be in demand due to their expertise in developing and applying AI models to complex scientific problems. Roles such as data scientists, AI researchers, and machine learning engineers are expected to persist because they require specialized knowledge, critical thinking, and ongoing innovation that AI tools complement rather than replace. These jobs often involve interdisciplinary skills, programming, and understanding of domain-specific data, making them more resilient to automation.

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.

How much does a machine learning scientist make?

A machine learning scientist typically earns between $90,000 and $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in deep learning or natural language processing can earn higher salaries, often exceeding $180,000.

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.

Is 40 too late for data science?

Scientific Machine Learning roles often value skills and experience over age, and many professionals transition into data science or machine learning at various stages of their careers. Learning relevant tools like Python, TensorFlow, or scikit-learn and gaining practical experience can help regardless of age, making 40 not too late to pursue this field.
What are popular job titles related to Scientific Machine Learning jobs in Raleigh, NC? For Scientific Machine Learning jobs in Raleigh, NC, the most frequently searched job titles are:
What cities near Raleigh, NC are hiring for Scientific Machine Learning jobs? Cities near Raleigh, NC with the most Scientific Machine Learning job openings:
Infographic showing various Scientific Machine Learning job openings in Raleigh, NC as of June 2026, with employment types broken down into 78% Full Time, and 22% Part Time. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $63,645 per year, or $30.6 per hour.

Machine Learning Engineer

CoVar

Durham, NC • On-site

Full-time

Posted yesterday


Job description

Job Summary:
CoVar is a small AI/ML R&D software company in Durham, NC, that uses artificial intelligence to solve problems that matter. In this role, you will help develop software and machine learning algorithms to address real-world customer challenges, working closely with data and presenting your findings to high-level customers.
Responsibilities:
• help CoVar develop software and machine learning algorithms to solve real-world customer problems
• work with data, develop algorithms, evaluate results, and write the production code that goes onto real-world systems
• present your work to high-level customers in the DoD and in the industry
• opportunities to publish novel work in both classified and unclassified settings.
Qualifications:
Required:
• Expertise in Python (including NumPy, pandas, and other packages)
• Experience with either PyTorch or TensorFlow
• Deep understanding of machine learning fundamentals (gradient descent, cross-validation, ROC curves, confusion matrices)
• Knowledge of classical machine learning (e.g., support-vector-machines, logistic regression)
• Familiarity with computer vision algorithms like object detection networks (e.g., YOLO, CenterNet) and modern image classification techniques
• Software expertise: Python and associated numerical and analytics packages (NUMPY, PANDAS, etc.); git; PYTORCH or TensorFlow; CI/CD pipelines and regression testing
• AI/ML expertise: Machine learning fundamentals; Deep knowledge of state-of-the-art in any of the following: computer vision (preferred), natural language processing, classical machine learning, Bayesian models, etc.
• B.S., preferably M.S. or Ph.D in engineering, math, computer science, or related field
• Excellent technical communication skills
• Ability to work in Durham, NC (relocation assistance available)
• Eligibility for US security clearance (US citizenship is required)
Preferred:
• Previous experience with DoD customers
• Department of Defense project experience
• Active US security clearance (secret or higher)
Company:
CoVar is a leader in machine learning and artificial intelligence solutions. Founded in 2011, the company is headquartered in Mclean, USA, with a team of 11-50 employees. The company is currently Early Stage.