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Machine Learning Engineer Jobs in Columbia, SC (NOW HIRING)

Machine Learning Engineer

North, SC ยท Remote

$197K - $270K/yr

About The RoleAs a Machine Learning Engineer, you'll do more than build models - you'll design the systems that make fraud detection possible. You'll work across modeling, data pipelines, and backend ...

We are seeking a Staff Machine Learning Engineer to join our dynamic team specializing in a technology marketplace platform for engineering talent and delivering cutting-edge Generative AI (GenAI ...

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

Implement machine learning pipelines for scalable model training and inference. * Tune and optimize models for performance and efficiency, including hyperparameter tuning, model evaluation, and ...

New

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

CTIO-AI Engineer-Sr Associate

Columbia, SC ยท On-site

$55K - $187K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

NGA AI Engineer Manager

Columbia, SC ยท On-site

$73.50K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

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Machine Learning Engineer information

See Columbia, SC salary details

$29.1K

$119.1K

$179K

How much do machine learning engineer jobs pay per year?

As of Jun 4, 2026, the average yearly pay for machine learning engineer in Columbia, SC is $119,129.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,900.00 and $143,400.00 per year, depending on experience, location, and employer.

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 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.

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 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 jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.

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 Columbia, SC? The most popular types of Machine Learning Engineer jobs in Columbia, SC are:
What are popular job titles related to Machine Learning Engineer jobs in Columbia, SC? For Machine Learning Engineer jobs in Columbia, SC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Columbia, SC look for? The top searched job categories for Machine Learning Engineer jobs in Columbia, SC are:
What cities near Columbia, SC are hiring for Machine Learning Engineer jobs? Cities near Columbia, SC with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Columbia, SC as of May 2026, with employment types broken down into 1% Internship, 53% Full Time, 44% Part Time, and 2% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $119,129 per year, or $57.3 per hour.
Machine Learning Engineer

Machine Learning Engineer

SARDINE

North, SC โ€ข Remote

$197K - $270K/yr

Full-time

Dental, Vision, Retirement, PTO

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Get AI-powered advice on this job and more exclusive features.Who We AreWe are a leader in fraud prevention and AML compliance. Our platform uses device intelligence, behavior biometrics, machine learning, and AI to stop fraud before it happens. Today, over 300 banks, retailers, and fintechs worldwide use Sardine to stop identity fraud, payment fraud, account takeovers, and social engineering scams.

We have raised $145M from world-class investors, including Andreessen Horowitz, Activant, Visa, Experian, FIS, and Google Ventures.Our CultureWe have hubs in the Bay Area, NYC, Austin, and Toronto. However, we maintain a remote-first work culture. #WorkFromAnywhereWe hire talented, self-motivated individuals with extreme ownership and high growth orientation.We value performance and not hours worked.

We believe you shouldn't have to miss your family dinner, your kid's school play, friends get-together, or doctor's appointments for the sake of adhering to an arbitrary work schedule.LocationRemote โ€“ United States or CanadaFrom Home / Beach / Mountain / Cafe / Anywhere!We are a remote-first company with a globally distributed team. You can find your productive zone and work from there.About The RoleAs a Machine Learning Engineer, you'll do more than build models โ€“ you'll design the systems that make fraud detection possible. You'll work across modeling, data pipelines, and backend systems (Go) to ensure ML models run reliably, efficiently, and at scale.

This is a chance to combine applied ML with large-scale systems engineering, owning end-to-end solutions that tackle high-stakes, ever-evolving challenges.What You'll DoBuild and optimize data pipelines and backend services to process device and behavioral data in real time.Develop and deploy ML models for fraud detection, ensuring they run reliably and efficiently in production.Turn raw data into production-ready features that feed our fraud detection systems.Collaborate with platform and backend engineers to integrate models seamlessly.Maintain high standards of security, privacy, and compliance.Champion best practices in testing, documentation, and observability.What You Bring5+ years in software engineering, with strong backend experience (Go or Python).Hands-on experience with applied ML using large datasets (PyTorch, Scikit-learn, etc.).Strong SQL skills and familiarity with relational and non-relational databases.Experience with end-to-end ML systems: feature pipelines, model deployment, monitoring, and iteration.Excellent communication skills in English, both written and verbal.Bachelor's or Master's in Computer Science, Engineering, or a related discipline.Bonus PointsDomain knowledge in fraud, risk, or cybersecurity.Familiarity with CI/CD, Docker, Kubernetes and the modern devops framework.Understanding of modern browser APIs and high-entropy data collection techniques.Familiarity with leveraging frontier LLMs for automation.Compensation: Base pay range of $170,000 โ€“ $200,000 USD / $197,000 โ€“ $270,000 CAD + equity with tremendous upside potential + Attractive benefitsBenefits We OfferGenerous compensation in cash and equityEarly exercise for all options, including pre-vestedWork from anywhere: Remote-first CultureFlexible paid time off, Year-end break, Self care days offHealth insurance, dental, and vision coverage for employees and dependents โ€“ US and Canada specific4% matching in 401k / RRSP โ€“ US and Canada specificMacBook Pro delivered to your doorOne-time stipend to set up a home office โ€“ desk, chair, screen, etc.Monthly meal stipendMonthly social meet-up stipendAnnual health and wellness stipendAnnual Learning stipendUnlimited access to an expert financial advisoryJoin a fast-growing company with world-class professionals from around the world. If you are seeking a meaningful career, you found the right place, and we would love to hear from you.To learn more about how we process your personal information and your rights in regards to your personal information as an applicant and Sardine employee, please visit our Applicant and Worker Privacy Notice.Seniority LevelMid-Senior levelEmployment TypeFull-timeJob FunctionEngineering and Information TechnologyJ-18808-Ljbffr