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Machine Learning Engineer Jobs in Hinesville, GA

MHI

Engineering Machining Manager

Pooler, GA · On-site

... learning. * Set clear performance expectations aligned to safety, quality, delivery, and cost ... Optimize cycle times, machine utilization, and process capability (Cp/Cpk). * Ensure integration of ...

Broetje Automation

Startup Engineer

Savannah, GA · On-site

$34 - $43/hr

Strong fundamental understanding of electrical design practices, machine/motion control systems, electro-mechanical systems, robotics, programming, and system integration * Understanding of PLC ...

Broetje Automation

Startup Engineer

Savannah, GA · On-site

$34 - $43/hr

Strong fundamental understanding of electrical design practices, machine/motion control systems, electro-mechanical systems, robotics, programming, and system integration * Understanding of PLC ...

Yancey Bros.co

Heavy Equipment Training Instructor

Pooler, GA · On-site

$51K - $68K/yr

... learning more about our customers, offering equipment and support to keep up with their changing ... Lectures classes on safety, installation, programming, testing, maintenance and repair of machinery ...

Yancey Bros Co

Heavy Equipment Training Instructor

Pooler, GA · On-site

$51K - $68K/yr

... learning more about our customers, offering equipment and support to keep up with their changing ... Lectures classes on safety, installation, programming, testing, maintenance and repair of machinery ...

Hyundai Autoever America

MES Engineer III

Savannah, GA · On-site

$79K - $112K/yr

MES Engineer III Location: Savannah, GA Company Overview Hyundai AutoEver America (HAEA) , the ... Our team is driven by a shared commitment to collaboration, innovation, and continuous learning. We ...

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

Machine Learning Engineer information

See Hinesville, GA salary details

$28.9K

$118.2K

$177.6K

How much do machine learning engineer jobs pay per year?

As of Jul 28, 2026, the average yearly pay for machine learning engineer in Hinesville, GA is $118,186.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,200.00 and $142,300.00 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 cities near Hinesville, GA are hiring for Machine Learning Engineer jobs? Cities near Hinesville, GA with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Hinesville, GA as of July 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $118,186 per year, or $56.8 per hour.

Smart Factory Engineer

HL-GA Battery Company LLC

Ellabell, GA • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description


Summary:
This position is responsible of applying Manufacturing Intelligence System to realize battery factory automation. This position will provide engineering support for Smart Factory System by project management and implementation of Autonomous Control System, Battery Cell Traceability System, ROS (Remote Operation System) etc. This role also will be able to communicate with cross-functional teams and individuals within the company.

Responsibilities:

  • Reviewing and implementing applications of Smart Factory system based on the latest technology.
  • Project management and deployment of key Smart Factory systems i.e. Remote Operation System, Autonomous Calibration, Product Traceability and Preventive Maintenance etc.
  • Participating SAT (Site Acceptance Test), Commissioning to functionality & performance check of smart factory systems once installed at equipment.
  • Planning strategies to improve equipment efficiency and availability based on automation (via PLC – Programmable Logic Controller) and manufacturing IT systems.
  • Weekly/Monthly Report (Issue/Achievement/Progress)
  • Conduct regular cadence meeting (weekly or monthly) to discuss issues/progress/achievement of the smart factory projects with parent headquarters.
  • Smart Factory Systems Investment & Operation Budget management
  • Others as directed


Qualifications:

  • Bachelor's Degree in Engineering (Electrical Engineering, Mechatronic Engineering, Computer Engineering, Computer Science, Data Analytics).


Experience:

  • In-depth understanding of network systems & IT (1 to 3+ years of professional experience is preferred).
  • Previous experience with data visualization tool such as Spotfire, Power BI etc,.
  • Knowledge and experience of Factory Automation (Programmable Logic Controller, Python, C#, Data Analytics, Feature Engineering etc) and Project Management (Schedule & Task progress management)
  • Experience of data analysis using Spotfire with manufacturing data base.
  • Internship or co-op experience in manufacturing or industrial environment will be considered in lieu of full-time experienc


Work Authorization:

  • Must be legally authorized to work in the United States without sponsorship.


Skills:

  • Proficient to use PC, MS Office [Word, Excel, PowerPoint].
  • Ability to use data visualization tool such as Spotfire, Power BI etc,.
  • IT System maintenance skill for SW/HW trouble shooting.
  • Ability to review and modify smart factory systems via Python, C# and PLC program.
  • Ability to communicate technical details both verbally and in writing.
  • Self-motivated, strong accountability and enthusiastic learner for dedicated smart factory systems and foundation technologies (PLC, Machine Learning, Network, Vision inspection etc), with keen attention to details.
  • Ability to work across multi-cultural environment and global distributed projects.
  • Strong analytical skills for root causes analysis when issue occurs and problem-solving skills by managing cross-functional team.
Physical Requirements:

Must be able to properly and regularly utilize the following PPE for a period of up to 12 hours:

  • Safety glasses
  • Steel-toed shoes
  • Nitrile gloves
  • Ear protection
  • Cleanroom suit

Must be able to perform the following activities repeatedly for periods of up to 12 hours:

  • Lift, push, and pull materials or equipment
  • Stoop, twist, and bend
  • Reach overhead
  • Sit and/or stand for extended periods
  • Use hands and fingers to operate tools, equipment, and computer systems

Work Environment:

  • Work may involve handling or working in proximity to hazardous materials and regulated industrial chemicals.
  • Exposure to chemical vapors, dust, or other controlled substances may occur depending on process assignment.
  • Strict adherence to company safety policies and OSHA Hazard Communication requirements is mandatory.
  • Employees must properly wear and maintain assigned personal protective equipment (PPE) at all times within designated areas.
  • Required PPE may include respirators, chemical-resistant garments, gloves, eye protection, face shields, or other equipment determined by process and risk assessment.


HL-GA Battery Company is an Equal Employment Opportunity (EEO) employer that values the diversity of its workforce.



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