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

Software Engineer - Machine Learning

Charlotte, NC · On-site

$95K - $130K/yr

... the machine learning function at a market-leading insurance company. As one of the first data ... Leverage continuous engineering practices to deliver business value regarding effectiveness of the ...

AI Solutions Architect

Charlotte, NC

$61.50 - $81/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Overall 8 to 10 years of solid experience in the areas of data engineering machine learning data science * 4 to 6 years of strong experience with the following machine learning topics classification ...

Proven experience in data science, machine learning, or predictive analytics roles * Proficiency in programming languages commonly used in data science (e.g., Python, R, etc.) * Experienced in using ...

Overview Machine Learning AI team seeking a ML Ops Engineer to drive the full lifecycle of machine learning solutions. Key Responsibilities * Develop and maintain ML pipelines using tools like MLflow ...

GEN AI Engineer

Charlotte, NC · On-site

$78K - $105K/yr

The role requires expertise in AI, machine learning, and software engineering to create maintainable and scalable solutions. Responsibilities : • Design, develop, and maintain applications that ...

Lead, AI Engineering

Charlotte, NC

$100K - $131K/yr

The team combines expertise in machine learning, generative AI, data engineering, and platform infrastructure to deliver innovative solutions that improve business outcomes and accelerate digital ...

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 ...

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 ...

Senior AI Engineer

Charlotte, NC

$102K - $140K/yr

This position blends applied machine learning, software engineering, cloud architecture, and end-to-end solution delivery. Success in this role requires a strong understanding that production AI ...

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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 Jul 9, 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 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 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:
Infographic showing various Machine Learning Engineer job openings in Fort Mill, SC as of July 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $113,156 per year, or $54.4 per hour.
Software Engineer - Machine Learning

Software Engineer - Machine Learning

CRC Group

Charlotte, NC • On-site

$95K - $130K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 29 days ago


Job description

The position is described below. If you want to apply, click the Apply button at the top or bottom of this page. You'll be required to create an account or sign in to an existing one.
If you have a disability and need assistance with the application, you can request a reasonable accommodation. Send an email to Accessibility (accommodation requests only; other inquiries won't receive a response).
Regular or Temporary:
Regular
Language Fluency: English (Required)
Work Shift:
1st Shift (United States of America)
Please review the following job description:
We are building the foundation of the machine learning function at a market-leading insurance company. As one of the first data science hires, you will play a pivotal role in shaping our ML strategy, frameworks, and operating model. This is a unique opportunity to be hands-on, developing and maintaining production-grade solutions while influencing the long-term vision and scaling of our ML capabilities.
Key Responsibilities
  • Strategic Contribution
    • Partner with the Head of ML, product and data teams to define and implement the company-wide ML framework and best practices.
    • Contribute to the roadmap for ML development, adoption and team growth.
  • Hands-On Development
    • Ideate, design and build ML and AI prototypes to validate priority use cases and solve complex business problems to drive tangible value, while collaborating with product and business teams.
    • Develop and deploy production-grade ML models and data pipelines.
    • Build orchestration and integration frameworks for ML models and pipelines.
    • Develop and maintain CI/CD pipelines for ML solutions, including test automation, to ensure successful deployment of updated models
  • Operational Excellence
    • Monitor, maintain, and retrain models in production to ensure performance and compliance.
    • Manage data updates, versioning, and integrity for deployed solutions.
    • Implement robust monitoring and alerting systems for ML services.
  • Team Building
    • Help establish processes, tools, and standards for a growing ML team.
    • Mentor future hires and contribute to a collaborative, innovative culture.

ESSENTIAL DUTIES AND RESPONSIBILITIES
Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.
1. Develop customized coding, software integration, perform analysis, configure solutions, using tools specific to the project or the area.
2. Lead and participate in the development, testing, implementation, maintenance, and support of highly complex solutions in adherence to company standards, including robust unit testing and support for subsequent release testing.
3. Build non-functional monitoring capabilities and provide escalated support for highly complex applications in production.
4. Build in and maintain security controls and monitoring in support of company standards.
5. Typically lead moderately complex projects and participate in larger, more complex initiatives.
6. Solve complex technical and operational problems. Act as a resource for teammates with less experience
7. May oversee the work of a small team.
8. In an Agile environment: Responsible for delivering high quality working software and automating manual/reusable tasks working directly, and engage with, the business from the beginning of the design work. Leverage continuous engineering practices to deliver business value regarding effectiveness of the design. Actively participate in refining user stories. Responsible for design, developing, and maintaining automated unit testing, and supporting integration and functional testing. Responsible for providing automated monitoring capabilities, providing warranty support, and providing knowledge transfer to production support. Develop code in accordance with the acceptance criteria established by the Product Owner.
QUALIFICATIONS
Required Qualifications:
The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
1. Bachelor's Degree and six to ten years of experience or equivalent education and software engineering training or experience
  • Technical Skills
    • Strong proficiency in Python and ML frameworks.
    • Experience with Databricks and Azure for data engineering and ML workflows.
    • Familiarity with MLOps tools (MLflow, Lakehouse Monitoring, Azure DevOps) and CI/CD practices.
    • Solid understanding of data science and engineering principles and model lifecycle management.
  • Experience
    • 5+ years total in data analytics, infrastructure, engineering and science roles.
    • 2+ years in applied ML engineering or data science roles.
    • Proven track record of deploying ML models into production environments.
    • Familiarity with monitoring, retraining, and maintaining ML systems at scale.
  • Soft Skills
    • Ability to work independently and collaboratively in a fast-paced environment.
    • Strong communication skills to influence stakeholders and explain technical concepts.
  • Nice-to-Have:
    • Knowledge of insurance industry data and business processes

2. In-depth knowledge in information systems and ability to identify, apply, and implement best practices
3. Understanding of key business processes and competitive strategies related to the IT function
4. Ability to plan and manage projects and solve complex problems by applying best practices
5. Ability to provide direction and mentor less experienced teammates. Ability to interpret and convey complex, difficult, or sensitive information
Location note: this role is hybrid based in the posted locations, and we are open to remote for the right candidate.
#LI1
#LI-MW1
General Description of Available Benefits for Eligible Employees of CRC Group: At CRC Group, we're committed to supporting every aspect of teammates' well-being - physical, emotional, financial, social, and professional. Our best-in-class benefits program is designed to care for the whole you, offering a wide range of coverage and support. Eligible full-time teammates enjoy access to medical, dental, vision, life, disability, and AD&D insurance; tax-advantaged savings accounts; and a 401(k) plan with company match. CRC Group also offers generous paid time off programs, including company holidays, vacation and sick days, new parent leave, and more. Eligible positions may also qualify for restricted stock units and/or a deferred compensation plan.
CRC Group supports a diverse workforce and is an Equal Opportunity Employer that does not discriminate against individuals on the basis of race, gender, color, religion, citizenship or national origin, age, sexual orientation, gender identity, disability, veteran status or other classification protected by law. CRC Group is a Drug Free Workplace.
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