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Scientific Machine Learning Jobs in Georgia (NOW HIRING)

KSB, Inc.

Machine Learning Engineer

Grovetown, GA · On-site

The role lives where machine learning meets scientific computing: surrogate modeling, data-driven approximations of physical systems, and ML models that respect the underlying engineering principles.

Ksb

Machine Learning Engineer

Grovetown, GA · On-site

The role lives where machine learning meets scientific computing: surrogate modeling, data-driven approximations of physical systems, and ML models that respect the underlying engineering principles.

Equifax, Inc.

Machine Learning Engineer

Atlanta, GA · On-site

Equifax is excited to add a Machine Learning Engineer to our team. What you'll do * Design complex ... Collaboration - Being able to engage with internal stakeholders, including data scientists ...

Saince, Inc.

Machine Learning Scientist

Alpharetta, GA · On-site

Company Description Saince (pronounced Science) is a leading clinical documentation solutions and ... Research, design and prototype novel models based on machine learning, data mining, and statistical ...

Saince, Inc.

Machine Learning Scientist

Alpharetta, GA · On-site

Company Description Saince (pronounced Science) is a leading clinical documentation solutions and ... Research, design and prototype novel models based on machine learning, data mining, and statistical ...

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

Machine Learning Engineer Employment Type: Full Time Location: Atlanta, GA Description We are ... Work cross-functionally with R&D, Data Science, Product, and Engineering to deliver business ...

Athena Technology Group, Inc. (ATG)

ATG is an Equal Opportunity/Affirmative Action Employer Minorities/Females/Vets/Disability Job Summary We are seeking a Data Scientist / Machine Learning Engineer to support advanced analytics and ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Georgia

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 Georgia?

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

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

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

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

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

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 21% Part Time, 6% Contract, and 3% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Data Scientist/Machine Learning Scientist

Atlanta, GA • On-site

The Intersect Group
See more jobs at The Intersect Groupexternal

Other

This job post has expired today. Applications are no longer accepted.

Job description

Position Overview

We are seeking a Data Scientist / Machine Learning Scientist to join a centralized AI and Data Science team supporting multiple business units across the organization. This role will partner with business leaders, product teams, and technical stakeholders to identify opportunities where advanced analytics and machine learning can create strategic value.

The ideal candidate is passionate about solving complex business challenges through data driven insights and predictive modeling. You will be responsible for developing, deploying, and optimizing machine learning solutions while helping shape the organization's AI and analytics capabilities. This position offers the opportunity to work across a variety of business domains and influence high impact initiatives from concept through production.

Key Responsibilities

• Collaborate with business stakeholders, product teams, and technology partners to identify and prioritize data science opportunities

• Design, develop, deploy, and maintain machine learning models that address complex business challenges

• Perform exploratory data analysis to evaluate data quality, identify trends, and uncover actionable insights

• Build predictive, classification, clustering, and optimization models using advanced statistical and machine learning techniques

• Monitor model performance and continuously refine solutions throughout the model lifecycle

• Translate business requirements into scalable data science solutions and clearly communicate results to technical and nontechnical audiences

• Develop scalable data science workflows utilizing cloud platforms and big data technologies

• Stay current on emerging AI, machine learning, and advanced analytics technologies and recommend innovative solutions where appropriate

Key Requirements

• Bachelor's, Master's, or PhD in Computer Science, Statistics, Data Science, Mathematics, Machine Learning, Engineering, or a related quantitative field

• Proven experience developing, deploying, and maintaining machine learning models in production environments

• Strong programming expertise with Python and experience with Scala

• Advanced SQL skills and experience working with large scale structured and unstructured datasets

• Hands on experience with big data technologies including PySpark, Apache Spark, and distributed data processing environments

• Deep understanding of statistical analysis, predictive modeling, feature engineering, model validation, and machine learning methodologies

• Experience communicating technical concepts and analytical findings to both technical and business stakeholders

• Strong problem solving skills with the ability to work independently and collaboratively across cross functional teams

Preferred Qualifications

• Experience with supervised and unsupervised machine learning techniques

• Expertise with Random Forest, Gradient Boosting Machines, XGBoost, Support Vector Machines, K Means Clustering, and DBSCAN

• Experience building and deploying deep learning models

• Knowledge of cloud based data science and machine learning platforms

• Experience designing scalable analytics pipelines and automation processes

• Strong background in predictive analytics, data mining, and advanced statistical modeling

• Experience creating data visualizations and presenting insights to executive leadership

Work Arrangement

• Atlanta based candidates will work a hybrid schedule with 2 days per week onsite

• Candidates located outside the Atlanta area may work fully remote

Why Join This Opportunity

• Work on high visibility AI and machine learning initiatives with enterprise wide impact

• Collaborate with experienced data scientists, engineers, product leaders, and business stakeholders

• Build innovative solutions using modern data science and machine learning technologies

• Influence strategic decision making through advanced analytics and predictive insights

• Enjoy the flexibility of a hybrid or remote working environment

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