1

Machine Learning Engineer Jobs in Charleston, SC

Machine Learning Engineer

Mount Pleasant, SC · On-site

$109K - $131K/yr

SynergisticIT is looking for candidates interested in ML/AI programming, Python, machine learning, NLP, model evaluation, APIs, data pipelines, automation, and AI application development. This role ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Charleston, SC · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

AI Engineer

Ladson, SC

$111K - $134K/yr

Designs and implements AI and machine learning solutions to improve manufacturing and business ... Collaborate with engineering and operations teams to integrate AI solutions into existing systems ...

AI Engineer

Ladson, SC

$111K - $134K/yr

Designs and implements AI and machine learning solutions to improve manufacturing and business ... Collaborate with engineering and operations teams to integrate AI solutions into existing systems ...

next page

Showing results 1-20

Machine Learning Engineer information

See Charleston, SC salary details

$29.5K

$120.5K

$181.1K

How much do machine learning engineer jobs pay per year?

As of Jul 8, 2026, the average yearly pay for machine learning engineer in Charleston, SC is $120,504.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,000.00 and $145,100.00 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.

What are the most commonly searched types of Machine Learning Engineer jobs in Charleston, SC? The most popular types of Machine Learning Engineer jobs in Charleston, SC are:
What are popular job titles related to Machine Learning Engineer jobs in Charleston, SC? For Machine Learning Engineer jobs in Charleston, SC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Charleston, SC look for? The top searched job categories for Machine Learning Engineer jobs in Charleston, SC are:
What cities near Charleston, SC are hiring for Machine Learning Engineer jobs? Cities near Charleston, SC with the most Machine Learning Engineer job openings:
Machine Learning Engineer

Machine Learning Engineer

SynergisticIT

Mount Pleasant, SC • On-site

$109K - $131K/yr

Other

Posted 5 days ago


Job description

ML/AI Programmer — Build Practical AI Skills Employers Understand AI is one of the most exciting areas in tech, but employers are not simply looking for candidates who have watched AI videos or completed a few notebooks. They want programmers who understand data, write clean Python code, evaluate models, connect AI work to applications, and explain results clearly. For entry-level candidates, practical proof matters.

SynergisticIT is looking for candidates interested in ML/AI programming, Python, machine learning, NLP, model evaluation, APIs, data pipelines, automation, and AI application development. This role is ideal for motivated learners who want to build a stronger foundation for AI-related software and data roles. Since 2010, Synergisticit has helped thousands of candidates land full-time jobs at tech leaders like Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Client, Paypal, Banking, Wayfair, Client, Client and hundreds more with Job offers of $95k to $154k.

Synergisticit focuses on closing the gap between your tech skills and what employers want now. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/Data Engineers/ Data Scientists, Machine Learning engineers for full time positions with clients. We Focus on Java /Full stack/Devops and Data Science /Data Engineers/Data analysts/BI Analysts/ Machine learning/AI candidates Ideal Candidates: Recent grads in CS, Engineering, Math, or Statistics with limited or no job experience Jobseekers who had layoffs due to Downsizing and want to get in demand tech stack Professionals seeking a career switch to tech Candidates with career gaps or lacking real-world experience Individuals looking to boost their skill portfolio for better job prospects Computer Science grads with limited or no job experience Students who recently finished their Bachelor's or Master's programs Those struggling to land interviews despite having experience Please check below links: Event videos (OCW, JavaOne, Gartner): https://fast.wistia.com/embed/channel/k4mlq69ekl USA Today feature Client JOPP: https://www.synergisticit.com/jopp/ Contact: https://www.synergisticit.com/contact-us/ please read our blogs Why do Tech Companies not Hire recent Computer Science Graduates | https://www.synergisticit.com/why-tech-companies-dont-hire-recent-cs-graduates/ Technical Skills or Experience?

| Which one is important to get a Job? | https://www.synergisticit.com/tech-skill-or-experience-which-one-is-more-important-for-a-jobseeker/ SynergisticIT JOPP is good for ML/AI candidates because it helps them move beyond theory and build a job-ready profile. Candidates can focus on practical projects, employer-aligned skills, technical interview preparation, and resume positioning that shows they can apply AI concepts in real-world contexts.

If you want to turn AI interest into practical career preparation, Contact us Please note: Resume databases are shared with clients and interested clients will reach out directly if they find a qualified candidate for their req. Resume submissions may be shared with our JOPP team database also. Please unsubscribe if contacted or if you don't want to be contacted please don't submit your resume.