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Scientific Machine Learning Jobs in Salisbury, NC

Teladoc

Senior Machine Learning Scientist

Concord, NC · On-site +1

Summary of Position The Machine Learning effort is part of the Data Science team at Teladoc Health. In this role, you will partner with Product, Engineering, Clinical,Operations, Marketing and Data ...

Varsity Tutors

Machine Learning Tutor

Winston Salem, NC · 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 ...

Varsity Tutors

Machine Learning Tutor

Charlotte, NC · 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 ...

Judi Health

Senior Machine Learning Engineer

Charlotte, NC · On-site

$161K - $202K/yr

Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative field. * Minimum 4+ years of experience in industry with a strong focus on ML solutions development and ...

Socket.dev

Senior Machine Learning Engineer

Charlotte, NC · On-site

$135 - $169/hr

Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative field. * Minimum 4+ years of experience in industry with a strong focus on ML solutions development and ...

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Crowe LLP

Machine Learning Intern

Charlotte, NC · On-site

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Crowe LLP

Machine Learning Intern

Charlotte, NC · On-site

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

CRC Group

Machine Learning Engineer

Charlotte, NC · On-site

$140 - $180/hr

## Machine Learning EngineerApplylocations: Charlotte NC - 600 S Tryon St.: Morrisville NC, 3015 ... As one of the first data science hires, you will play a pivotal role in shaping our ML strategy ...

Staffingine LLC

Data Scientist

Charlotte, NC · On-site

Expertise in machine learning statistical modelling and data thoughtfulness to develop and implement advanced algorithms and thoughtful solutions * Manage end-to-end data science projects ensuring ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Salisbury, NC

Scientific Machine Learning information

See Salisbury, NC salary details

$12

$28

$47

How much do scientific machine learning jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for scientific machine learning in Salisbury, NC is $28.45, according to ZipRecruiter salary data. Most workers in this role earn between $17.40 and $36.30 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 job categories do people searching Scientific Machine Learning jobs in Salisbury, NC look for?

The top searched job categories for Scientific Machine Learning jobs in Salisbury, NC are:

What cities near Salisbury, NC are hiring for Scientific Machine Learning jobs?

Cities near Salisbury, NC with the most Scientific Machine Learning job openings:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Salisbury, NC as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $59,178 per year, or $28.5 per hour.

Data Scientist / Machine Learning Engineer (Generative AI Focus)

Strategic Staffing Solutions

Charlotte, NC • On-site, Remote

Full-time

Re-posted 12 days ago

Job description

Job Description STRATEGIC STAFFING SOLUTIONS HAS AN OPENING. This is a Contract Opportunity with our company that MUST be worked on a W2 Only. No C2C eligibility for this position.

Visa Sponsorship is Available. The details are below. "Beware of scams.

S3 never asks for money during its onboarding process." Job Title: Data Scientist / Machine Learning Engineer (Generative AI Focus) Contract Length: 12+ Months Hybrid schedule 3 days per week onsite/ 2 remote Location: Charlotte, NC/ Irving, TX/ Boston, MA Ref# 246769 We are seeking a highly motivated Data Scientist / Machine Learning Engineer to build advanced analytics and Generative AI (Gen AI) solutions across multiple business functions. This role combines strong data analysis capabilities with machine learning and emerging Gen AI techniques to drive business insights, automation, and innovation. The ideal candidate is hands-on, analytical, and comfortable owning the full lifecycle of data science solutions-from problem definition through model development and deployment-while collaborating closely with engineering and business stakeholders

Key Responsibilities Perform in-depth data analysis and exploration using SQL and statistical techniques to uncover patterns, solve business problems, and support data-driven decision-making. Work with large, complex datasets while ensuring data quality, integrity, and usability. Design, develop, and implement scalable solutions using Python or Java.

Utilize data science and machine learning libraries such as NumPy, SciPy, Matplotlib, and Scikit-learn. Build reusable pipelines for data processing, feature engineering, and model evaluation. Develop and evaluate machine learning models, including tree-based and ensemble algorithms such as Random Forest and XGBoost.

Assess model performance, tune hyperparameters, and ensure models meet business and technical requirements. Apply AI-assisted techniques to enhance productivity and insights. Craft effective prompts using Gemini or similar generative AI models to support data exploration, feature generation, analysis, and summarization.

Communicate insights through visualizations, reports, and presentations. Translate complex technical findings into actionable business recommendations. Partner closely with engineering teams for implementation and business stakeholders to ensure alignment with strategic objectives.

Required Qualifications Strong SQL and data analysis skills. Experience working with structured and semi-structured datasets. Proficiency in Python or Java for data science, machine learning, and analytical workloads.

Hands-on experience with machine learning frameworks and model development. Experience building, training, and evaluating predictive models in production or near-production environments. Ability to work independently and own initiatives end-to-end, from problem definition and requirements gathering through solution delivery and validation.

Experience using generative AI models to augment analytical workflows. Familiarity with prompt engineering. Experience leveraging large language models (LLMs) for automation and analytical tasks.

Experience integrating Gen AI capabilities into analytical processes. Generative AI Focus Develop and deploy Gen AI solutions that enhance productivity, automate workflows, and generate AI-driven business insights. Apply foundational knowledge of Gen AI concepts, tools, and use cases.

Experience with large language models (LLMs), prompt engineering, or AI-assisted analytics. Strong interest in emerging AI technologies and a willingness to continuously learn and apply new Gen AI innovations. Preferred Qualifications Experience working in financial services, banking, or capital markets environments.

Experience in data-driven or risk-focused domains. Familiarity with cloud platforms. Experience with data engineering pipelines.

Familiarity with model deployment frameworks. Exposure to big data technologies. Experience with distributed computing environments.

Exposure to real-time analytics environments. Ideal Candidate Profile Self-driven data professional with strong analytical and problem-solving skills. Combines practical machine learning expertise with emerging AI capabilities.

Comfortable navigating ambiguous problems and translating business needs into technical solutions. Capable of delivering measurable business outcomes. Strong communication skills with both technical and non-technical stakeholders.

Passionate about applying traditional machine learning and modern Generative AI techniques to solve complex business challenges.

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