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Machine Learning Engineer Jobs in Augusta, GA (NOW HIRING)

DataAnnotation

SDLC Engineer - AI Trainer

Augusta, GA · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

Textron

Data Scientist

Augusta, GA · On-site

Builds, tests, and refines statistical and machine learning models using established methodologies ... Partners with engineering, IT, and business stakeholders to deploy analytics solutions into ...

New

Textron

Data Scientist

Augusta, GA · On-site

Builds, tests, and refines statistical and machine learning models using established methodologies ... Partners with engineering, IT, and business stakeholders to deploy analytics solutions into ...

New

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Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Augusta, GA

Machine Learning Engineer information

See Augusta, GA salary details

$24.8K

$101.5K

$152.5K

How much do machine learning engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for machine learning engineer in Augusta, GA is $101,470.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,000.00 and $122,100.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Augusta, GA? The most popular types of Machine Learning Engineer jobs in Augusta, GA are:
What are popular job titles related to Machine Learning Engineer jobs in Augusta, GA? For Machine Learning Engineer jobs in Augusta, GA, the most frequently searched job titles are:
What cities near Augusta, GA are hiring for Machine Learning Engineer jobs? Cities near Augusta, GA with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Augusta, GA as of July 2026, with employment types broken down into 85% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $101,470 per year, or $48.8 per hour.
Data Scientist - multiple levels - CLEARANCE and POLYGRAPH REQUIRED

Data Scientist - multiple levels - CLEARANCE and POLYGRAPH REQUIRED

Constellation Technologies, Inc

Augusta, GA

$120K - $220K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 5 days ago

Job description

Big Data, dataflows, Artificial Intelligence / Machine Learning (AI/ML) familiarity, Analytics in GME, Jupyter notebooks, and Spark.
 
Due to federal contract requirements, United States citizenship and an active TS/SCI security clearance and polygraph are required for the position.
 
 
Required:
  • Must be a US Citizen
  • Must have TS/SCI clearance w/ active polygraph
  • This position is open to multiple levels of years of experience; two (02) years within the last five (05) years must be directly related to the job you are applying for:
  • Level 04 requires a minimum seventeen (17) years of experience w/ Degree
  • Level 03 requires a minimum twelve (12) years of experience w/ Degree
  • Level 02 requires a minimum five (05) years of experience w/ Degree
  • Degree in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science. A degree in a related field (e.g., Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g., physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e., behavioral, social, and life) may be considered if it includes a concentration of coursework (typically 5 or more courses) in advanced mathematics (typically 300 level or higher; such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g., algorithms, programming, data structures, data mining, artificial intelligence). College-level Algebra or other math courses intended to meet a basic college level requirement, or upper-level math courses designated as elementary or basic do not count.
  • Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g., Python) and skill in at least one mid-level language (e.g. C)), data mining, advanced statistical analysis (e.g. statistical foundations of machine learning, statistical approaches to missing data, time series), advanced mathematical foundations (e.g. numerical methods, graph theory), artificial intelligence, workflow and reproducibility, data management and curation, data modeling and assessment (e.g. model selection, evaluation, and sensitivity.
  • Employ some combination (2 or more) of the following areas: Foundations (Mathematical, Computational, Statistical); Data Processing (Data management and curation, data description and visualization, workflow, and reproducibility); Modeling, Inference, and Prediction (Data modeling and assessment, domain-specific considerations).
  • Devise strategies for extracting meaning and value from large datasets.
  • Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge.
  • Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent to Agency data holdings.
  • Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data.
  • Effectively communicate complex technical information to non-technical audiences.
  • Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting Agency collection, processing, storage and analytic capabilities and limitations.
These Qualifications Would be Nice to Have:
  • Fully Cleared polygraph is preferred
  • Knowledge of working with Big Data, dataflows, Machine Learning/Artificial Intelligence familiarity.
  • Analytics in GME, Jupyter notebooks, and Spark.
$120,000 - $220,000 a year
The pay range for this job, with multi-levels, is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
The benefits package:
 
Affordable healthcare options with 80% employer paid premium PLUS a company-funded HSA
Dental insurance with 100% employer paid premium
Vision with 80% employer paid premium
Employer paid Life insurance 100%
Employer paid Short-term and Long-term disability 100%
Annual training, continued education, and professional memberships reimbursement
Unlimited access to Red Hat Enterprise Linux, AWS, and NetApp training and accreditation
Annual reimbursement for technology i.e. phones, computers, printers, etc...
401(k) with company match up to 5% with 100% immediate vesting (after 90 days of employment)
 
The environment and perks:
 
Professional development investment and paid time off for training
Contract and work locations in Maryland, Virginia, Colorado, Texas, Utah, California, Florida and Hawaii.
Team building events throughout the year such as Destination Family Events, Holiday Party, Monthly Get-Togethers
Leadership Team engagement and mentorship
Performance Recognition Program
Complimentary branded apparel
 
Don't see a job opening that's the perfect fit? Apply to our General Position to join our talent pool for consideration for future opportunities.
 
Know someone else who may be a good fit? Refer them through the CTI External Referral Program and you could receive a one-time referral bonus of up to $10,000! Email [email protected] for more information.
 
Constellation Technologies is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, religion, creed, color, national origin, ancestry, sex (including pregnancy, childbirth, breastfeeding, or medical conditions related to pregnancy, childbirth, or breastfeeding), age, medical condition, marital or domestic partner status, sexual orientation, gender, gender identity, gender expression and transgender status, mental disability or physical disability, genetic information, military or veteran status, citizenship, low-income status or any other status or characteristic protected by applicable law. Job applicants can submit questions about CTI's equal employment opportunity policy to [email protected].
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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