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

This individual will work closely with software engineers, data scientists, and product teams to operationalize machine learning models, improve ML infrastructure, and support scalable analytics ...

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 ...

Machine Learning Engineer Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software ... 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 ...

Qualifications : Required : • Bachelor's degree or higher in Computer Science, Computer ... industry-standard machine learning frameworks (PyTorch, TensorFlow, Scikit-Learn, etc.). • ...

Machine Learning Engineer Q2 is a leading provider of digital banking and lending solutions to ... You'll work closely with data scientists and engineers to bring models into production ensuring ...

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 ...

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 ...

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 ...

Sr. Machine Learning Engineer

Durham, NC · On-site

$50.50 - $66.75/hr

Machine Learning Engineer As a Machine Learning Engineer, build and maintain large scale ML ... Engineering, Computer Science, etc.). * Experience in Object Oriented Programming (Java, Scala ...

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Scientific Machine Learning information

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How much do scientific machine learning jobs pay per hour?

As of May 28, 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.

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 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 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 Raleigh, NC? For Scientific Machine Learning jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Raleigh, NC look for? The top searched job categories for Scientific Machine Learning jobs in Raleigh, NC 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:

Machine Learning Engineer

ExtendMyTeam

Cary, NC

Full-time

Posted 8 days ago


Job description

Join a high-growth financial technology organization focused on building modern digital banking, payments, lending, and risk solutions for financial institutions and fintech partners. This team is investing in machine learning and analytics capabilities to help improve fraud detection, predictive insights, and operational decision-making across customer-facing products.

This is an opportunity to work on applied machine learning systems that directly support real-world fraud and risk workflows. The team owns solutions end-to-end and is focused on building scalable, production-ready ML applications that deliver measurable customer impact.

Position Summary

We are seeking a Machine Learning Engineer to help design, deploy, and support production machine learning systems within a collaborative engineering organization. This individual will work closely with software engineers, data scientists, and product teams to operationalize machine learning models, improve ML infrastructure, and support scalable analytics workflows.

This is a hands-on engineering role focused on production systems, model deployment, APIs, pipelines, and ML operations rather than purely research-oriented machine learning work.

Responsibilities

  • Build and maintain systems and pipelines supporting machine learning training, evaluation, inference, and monitoring

  • Deploy and support machine learning models in production environments

  • Write clean, scalable, maintainable, and well-tested Python code

  • Support monitoring, troubleshooting, and optimization of production ML systems and data pipelines

  • Collaborate cross-functionally with engineering, data science, and product teams to operationalize ML solutions

  • Improve the reliability, scalability, and performance of ML infrastructure and services

  • Contribute to tooling and processes that support the machine learning development lifecycle

  • Participate in code reviews, technical discussions, and collaborative problem solving

Required Qualifications

  • 2+ years of experience in machine learning engineering, software engineering, or related technical experience

  • Strong Python development experience

  • Experience working with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn

  • Experience deploying or supporting machine learning models in production environments

  • Experience writing clean, maintainable code and using version control tools such as Git

  • Exposure to cloud platforms such as AWS, GCP, or Azure

  • Understanding of taking machine learning models from research/development into production systems

Additional Information

  • Hybrid work environment based in Cary, NC

  • Applicants must be authorized to work in the U.S. without sponsorship

  • Competitive compensation, benefits, flexible time off, and career development opportunities