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

The Hartford

Senior AI Machine Learning Engineer

Charlotte, NC · On-site

$119K - $157K/yr

Sr Data Engineer - GE07BE We're determined to make a difference and are proud to be an insurance ... The Hartfordis seeking aSenior AI Machine Learning Engineerwithin Employee Benefits Applied AI and ...

Euclid Innovations

ML Engineer

Charlotte, NC · On-site

Euclid Innovations is seeking a skilled and experienced Machine Learning Engineer to design and implement solutions for extracting, processing, and storing information from large-scale document ...

Varsity Tutors

Machine Learning Tutor

Matthews, NC · Remote

$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 ...

Varsity Tutors

Machine Learning Tutor

Charlotte, NC · Remote

$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 ...

Judge Group, Inc.

Software Engineer

Charlotte, NC · On-site

$68 - $73/hr

Senior AI Platform Engineer (Contract) We are not accepting C2C or 1099 arrangements. Location ... Design, develop, and deploy scalable AI, Machine Learning, Generative AI, and Predictive AI ...

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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 Sep 14, 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 is a machine learning engineer?

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 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 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 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 September 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $113,156 per year, or $54.4 per hour.

Machine Learning/AI Engineering Manager

Charlotte, NC • On-site

Vangard, Inc.
Convention and Trade Show Organizers • 11 - 50 employees
Learn more about Vangard, Inc.external

Full-time

Posted 10 days ago

Job description

We are seeking a Machine Learning Engineering Manager to lead a high-performing team of Machine Learning Engineers responsible for building, operating, and evolving Vanguard's production AI, ML, and Generative AI solutions.

This leader will oversee engineering for a portfolio of traditional machine learning and GenAI capabilities that power investor personalization, financial planning, and advice experiences across Personal Wealth Technology. You will partner closely with Data Scientists, Product Owners, Architects, and Vanguard's Investment Strategy Group (ISG) methodology teams to transform sophisticated models and research into reliable, scalable, and trusted production solutions.

This is a highly technical leadership role. The successful candidate will be expected to actively participate in solution architecture, technical design, engineering strategy, model operations, production support, and Agile delivery while developing the next generation of AI engineering talent.

Responsibilities

  • Lead a team of Machine Learning Engineers delivering scalable, secure, reliable, and extensible AI solutions
  • Develop, maintain, support, and evolve a portfolio of production machine learning and generative AI models
  • Partner with Investment Strategy Group methodology teams to operationalize financial advice, portfolio construction, and personalization models
  • Ensure production readiness through monitoring, alerting, validation, testing, observability, and incident management practices
  • Drive engineering excellence, DevOps, MLOps, LLMOps, and FinOps disciplines
  • Shape AI and ML roadmaps alongside Data Scientists, Product Owners, and stakeholders
  • Provide technical direction and architectural guidance for complex AI and ML initiatives
  • Build trusted relationships across technology and business teams to influence strategy and delivery outcomes
  • Establish standards and best practices that enable safe, trustworthy, explainable, and scalable AI solutions
  • Drive adoption of GenAI and agentic solutions within the engineering organization to improve efficiency, automation, and delivery quality
  • Hire, coach, mentor, and develop future technical leaders

What You'll Own

  • Delivery, operation, and continuous improvement of Vanguard's production AI, ML, and GenAI platforms and solutions
  • Engineering ownership along with ISG Methodology for the Vanguard Financial Advice Model (VFAM) and Risk-Based Research Engine (RBRE)
  • Model health monitoring, observability, availability, and operational excellence across all production models
  • Reliability and support processes ensuring production AI systems remain resilient, trusted, and available
  • Technical leadership for Machine Learning Engineering, MLOps, LLMOps, DevOps, and FinOps practices
  • Team leadership, coaching, and development for a high-performing Machine Learning Engineering organization
  • Stakeholder relationships across Technology, Methodology, Product, and Analytics teams

Qualifications

  • Minimum of eight years data analytics, programming, database administration, or data management experience.
  • Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.

Preferred Qualifications

  • Proven experience leading Machine Learning, AI Engineering, or Software Engineering teams
  • Strong technical depth in production AI/ML systems and cloud-native engineering
  • Experience establishing operational excellence for production AI platforms
  • Demonstrated success partnering with product, analytics, and business stakeholders
  • Passion for developing engineering talent and building high-performing teams
  • Ability to balance strategic leadership with hands-on technical engagement
  • Interest in advancing modern engineering practices, including MLOps, LLMOps, FinOps, and agentic AI

Why This Role

  • Directly influence how Vanguard delivers personalized financial advice at scale
  • Lead engineering for some of Vanguard's most strategic AI and machine learning capabilities
  • Work at the intersection of financial methodology, applied AI, and large-scale engineering
  • Shape the future of GenAI, agentic systems, and AI engineering practices within Personal Wealth Technology
  • Develop a talented team while driving meaningful outcomes for millions of investors
  • Join a leadership team committed to innovation, engineering excellence, and investor-centric outcomes

Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission-we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

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