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Machine Learning Engineer Jobs in Fort Mill, SC (NOW HIRING)

HTC Global Services

AI Engineer

Charlotte, NC · On-site

This role focuses on Generative AI, Large Language Models (LLMs), Prompt Engineering, Agentic AI systems, Machine Learning, Data Science, and cloud-native engineering on AWS. The ideal candidate will ...

Deloitte

AI and Data Science Engineer II

Charlotte, NC · On-site

$111K - $134K/yr

Translating business goals into machine learning use cases and model design approaches ... Bachelor's degree in engineering, mathematics, physics, machine learning, statistics, computer ...

DPR Construction

MLOps Engineer

Charlotte, NC

We are looking for aMLOps Engineerto join our team and contribute to developing robust data solutionsto support our Machine Learning,Data Science, Data Engineering and Software Engineering. Position ...

Scout Motors Inc.

Lead, AI Engineering

Charlotte, NC · On-site

$100K - $131K/yr

... machine learning and generative AI models. • Design and oversee ETL/ELT pipelines in Python to ... engineering best practices for scalable AI solution delivery. Qualifications : Required : • ...

Deloitte

AI Data Engineer - Manager

Charlotte, NC

$111K - $134K/yr

AI Data Engineer - Manager Our Human Capital practice is at the forefront of transforming the ... Lead the development of AI models (e.g., machine learning, natural language processing, computer ...

Deloitte

Senior AI Engineer - SFL Scientific

Charlotte, NC · On-site

$102K - $140K/yr

Deloitte's Strategy & Transactions team is seeking a Senior AI Engineer to join SFL Scientific, a ... machine learning applications. Responsibilities : • Work with clients to design, develop, and ...

Deloitte

AI and Data Science Engineer III

Charlotte, NC · On-site +1

$111K - $134K/yr

Deliver governed datasets and feature engineering and serving patterns for machine learning training and real-time inference, including online and offline consistency, caching, latency targets, and ...

Pwc

CTIO AI Engineering Manager

Charlotte, NC

$73K - $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 ...

Deloitte

AI and Data Science Engineer III

Charlotte, NC · On-site

$111K - $134K/yr

They are seeking an AI and Data Science Engineer to build and operate data and AI foundations that ... machine learning training and real-time inference, including online and offline consistency ...

Pwc

NGA AI Engineer Manager

Charlotte, NC

$73K - $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 ...

Lorven Technologies

Python Developer AI/ML

Charlotte, NC · On-site

$49 - $67.75/hr

In this role, you will work closely with Senior Engineers, leads, and product teams to design scalable machine learning pipelines, optimize model performance, and deliver production ready AI ...

Pwc

CTIO-AI Engineer-Sr Associate

Charlotte, NC · 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 ...

Pwc

NGA AI Engineer Senior Manager

Charlotte, NC

$91K - $321K/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 ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Fort Mill, SC

Machine Learning Engineer information

See Fort Mill, SC salary details

$27.7K

$113.2K

$170K

How much do machine learning engineer jobs pay per year?

As of Jun 5, 2026, the average yearly pay for machine learning engineer in Fort Mill, SC is $113,156.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,200.00 and $136,200.00 per year, depending on experience, location, and employer.

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.

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 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 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.
More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Fort Mill, SC? The most popular types of Machine Learning Engineer jobs in Fort Mill, SC are:
What are popular job titles related to Machine Learning Engineer jobs in Fort Mill, SC? For Machine Learning Engineer jobs in Fort Mill, SC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Fort Mill, SC look for? The top searched job categories for Machine Learning Engineer jobs in Fort Mill, SC are:
What cities near Fort Mill, SC are hiring for Machine Learning Engineer jobs? Cities near Fort Mill, SC with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Fort Mill, 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 $113,156 per year, or $54.4 per hour.
Cybersecurity Engineer - Lead

Cybersecurity Engineer - Lead

IntraEdge

Charlotte, NC

Contractor

Posted 4 days ago

Job description

About the Role

Intraedge is seeking a seasoned Cybersecurity Engineer on behalf of its financial domain client to support advanced threat detection, data-driven defense, and automation within a cloud-first, consumer-centric environment.

This role will lead the development and implementation of intelligent security solutions using SIEM, SOAR, and machine learning to enhance detection, response, and operational efficiency across the enterprise.

Key Responsibilities
    *    Design, implement, and manage enterprise SIEM (Splunk) solutions for centralized log analysis and real-time event monitoring.
    *    Develop and fine-tune correlation rules, alerts, dashboards, and use cases to detect anomalous and malicious activity.
    *    Lead data ingestion and normalization from varied enterprise systems (e.g., cloud workloads, endpoints, network devices).
    *    Develop and maintain SOAR playbooks to automate incident detection, triage, response, and recovery.
    *    Optimize SOAR workflows and integrations with security infrastructure to reduce MTTD/MTTR.
    *    Build and apply machine learning models to identify security anomalies, enrich event context, and predict threats.
    *    Collaborate with Security Operations Center (SOC), DevOps, IT, and business units to align security automation with business goals.
    *    Analyze incident data to uncover trends and provide recommendations for improving controls and detection.
    *    Maintain detailed documentation for playbooks, integrations, automation processes, and incident response protocols.
    *    Stay abreast of industry trends and emerging tools to continually advance detection and automation strategies.
    *    Mentor junior engineers and assist in promoting SOAR and SIEM best practices across the team.

Required Qualifications
    *    6+ years of experience in cybersecurity engineering, including SIEM (Splunk), SOAR, and machine learning-based threat detection.
    *    3+ years of experience in security automation using platforms such as Splunk SOAR, XSOAR, Swimlane, or similar.
    *    3+ years in cyber data engineering or analytics: log processing, enrichment, and telemetry pipelines.
    *    Expertise in scripting languages like Python and PowerShell, and using REST APIs for integrations.
    *    Proven experience designing and deploying security automation workflows in enterprise environments.
    *    Bachelor's degree in Computer Science, Information Security, Engineering, or related field-or equivalent experience.
    *    Ability to troubleshoot complex security issues and integrate with diverse platforms.
    *    Strong communication and collaboration skills to work with technical and non-technical stakeholders.

Preferred Qualifications
    *    Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
    *    Familiarity with cloud-native security tooling, telemetry pipelines, and serverless security design patterns.
    *    Experience working within Agile environments and cross-functional DevSecOps teams.
    *    Knowledge of change management processes, compliance frameworks (e.g., NIST, ISO), and regulatory constraints in financial services.

Why Join This Engagement?
    *    Help build the next generation of cybersecurity automation for a major financial institution.
    *    Work with cutting-edge security architecture in a cloud-first, data-driven environment.
    *    Contribute to industry-leading practices in SOAR, ML-driven detection, and incident response automation.

Education:Employment Type: CONTRACTOR
IntraEdge logo

About IntraEdge

Sourced by ZipRecruiter

At heart, we are a technology, products and services organization In our soul, it’s the people who make us what we are — the professionals we train and connect to next-level opportunities and the experts who create innovative solutions and value for our national and international partners. It’s true that innovative technology can provide a major boost to your business, but you also need the right talent pushing it forward. This critical combination is what we offer all of our partners: cutting edge tech solutions and the expertise to bring it to life.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Chandler, AZ, US

Year founded

2002

Social media

Instagram

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