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Machine Learning Engineer Opt Jobs in Augusta, GA

KSB SE and Co KGaA

Automation Controls Engineer

Grovetown, GA · On-site

$76K - $101K/yr

Engineering Reports to: Senior Design Engineer Location: Grovetown, GA, USA (onsite) Shift: First ... Basic understanding of machine learning and data analysis methods * Basic understanding of ...

Ksb

Automation Controls Engineer

Grovetown, GA · On-site

$76K - $101K/yr

Engineering Reports to: Senior Design Engineer Location: Grovetown, GA, USA (onsite) Shift: First ... Basic understanding of machine learning and data analysis methods * Basic understanding of ...

Premier Packaging

Machine Operator Assistant

Thomson, GA · On-site

$17.85 - $19.85/hr

From corrugated, warehouse solutions, design & engineering to packaging supplies. Leave your past ... Be open to learning and gaining skills related to corrugated manufacturing processes. Benefits:

Prescient Edge

Senior Data Engineer

Augusta, GA · On-site

$98K - $133K/yr

Job Title Senior Data Engineer Location Augusta, GA 30905 US (Primary) Category Research ... machine learning, and data visualization communities. Education: * MA or MS in Data Science, Data ...

Varsity Tutors

Data Science Tutor

Augusta, GA · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

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

Machine Learning Engineer Opt information

See Augusta, GA salary details

$29.6K

$121K

$181.9K

How much do machine learning engineer opt jobs pay per year?

As of Aug 15, 2026, the average yearly pay for machine learning engineer opt in Augusta, GA is $121,044.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,400.00 and $145,700.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges machine learning engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What are popular job titles related to Machine Learning Engineer Opt jobs in Augusta, GA?

For Machine Learning Engineer Opt jobs in Augusta, GA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Opt jobs in Augusta, GA look for?

The top searched job categories for Machine Learning Engineer Opt jobs in Augusta, GA are:

What cities near Augusta, GA are hiring for Machine Learning Engineer Opt jobs?

Cities near Augusta, GA with the most Machine Learning Engineer Opt job openings:

Machine Learning Engineer Opt jobs near you
Infographic showing various Machine Learning Engineer Opt job openings in Augusta, GA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $121,044 per year, or $58.2 per hour.

Data Scientist - multiple levels - CLEARANCE and POLYGRAPH REQUIRED

Constellation Technologies, Inc

Augusta, GA

$120K - $220K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 12 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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