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Machine Learning Jobs in Rock Hill, SC (NOW HIRING)

Bespoke Labs

Machine Learning Engineer

Charlotte, NC · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

CRC Group

Machine Learning Engineer

Charlotte, NC · On-site

English (Required) Work Shift: 1st Shift (United States of America) Please review the following We are building the foundation of the machine learning function at a market-leading insurance company.

Tihinsurance

Machine Learning Engineer

Charlotte, NC · On-site

English (Required) Work Shift: 1st Shift (United States of America) Please review the following We are building the foundation of the machine learning function at a market-leading insurance company.

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All JobsMachine Learning JobsMachine Learning Jobs in Rock Hill, SC

Machine Learning information

See Rock Hill, SC salary details

$22.2K

$37.1K

$76.7K

How much do machine learning jobs pay per year?

As of Sep 2, 2026, the average yearly pay for machine learning in Rock Hill, SC is $37,126.00, according to ZipRecruiter salary data. Most workers in this role earn between $28,300.00 and $40,100.00 per year, depending on experience, location, and employer.

What is a machine learning?

A Machine Learning job involves developing algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. Professionals in this field work with large datasets, design and train machine learning models, and optimize them for performance and accuracy. Roles often require knowledge of programming languages like Python or R, experience with frameworks like TensorFlow or PyTorch, and an understanding of statistics and data science principles. Machine learning engineers and data scientists collaborate with software developers and domain experts to build AI-driven solutions for various industries.

What are the typical day-to-day responsibilities in a machine learning role?

As a machine learning professional, your daily tasks may include data preprocessing, developing and training models, evaluating performance metrics, and experimenting with algorithms to optimize results. You’ll often collaborate closely with data scientists, software engineers, and business stakeholders to align technical solutions with organizational goals. Regular activities can also involve deploying models to production, monitoring performance, and troubleshooting any issues that arise post-deployment. Staying up to date with recent ML research and participating in team discussions or code reviews are also common parts of the job.

What are the key skills and qualifications needed to thrive in a machine learning position?

To thrive in Machine Learning, you need a solid background in mathematics, statistics, programming (especially Python or R), and a formal degree in computer science, data science, or a related field. Experience with popular ML frameworks (such as TensorFlow, PyTorch, or Scikit-learn), version control, and relevant certifications like AWS Certified Machine Learning are highly valued. Strong problem-solving skills, curiosity, clear communication, and the ability to work both independently and within multidisciplinary teams make candidates stand out. These skills and qualities are essential for developing robust models, staying updated with technology advancements, and collaborating effectively on complex projects.

Is machine learning a high paying job?

Machine learning engineers and specialists are generally among the higher-paid roles in the tech industry due to their advanced skills in algorithms, programming, and data analysis. Salaries vary based on experience, location, and industry, but the field is known for competitive compensation compared to many other tech roles.

What jobs can I get with machine learning?

With a background in machine learning, you can pursue roles such as machine learning engineer, data scientist, AI researcher, or data analyst. These positions typically require skills in programming languages like Python or R, knowledge of algorithms, and experience with tools like TensorFlow or PyTorch.

What are the most commonly searched types of Machine Learning jobs in Rock Hill, SC?

The most popular types of Machine Learning jobs in Rock Hill, SC are:

What are popular job titles related to Machine Learning jobs in Rock Hill, SC?

For Machine Learning jobs in Rock Hill, SC, the most frequently searched job titles are:

What job categories do people searching Machine Learning jobs in Rock Hill, SC look for?

The top searched job categories for Machine Learning jobs in Rock Hill, SC are:

What cities near Rock Hill, SC are hiring for Machine Learning jobs?

Cities near Rock Hill, SC with the most Machine Learning job openings:

Machine Learning jobs near you
Infographic showing various Machine Learning job openings in Rock Hill, SC as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Contract, and 1% Nights. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $37,126 per year, or $17.8 per hour.

Machine Learning Engineer

Bespoke Labs

Charlotte, NC • On-site

Full-time

Re-posted 17 days ago

Job description

  • Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch

  • Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment orchestration

  • Run and scale training experiments on cloud or HPC (AWS, GCP, SLURM, Ray), and debug throughput, stability, and convergence issues

  • Build evaluation harnesses and benchmark infrastructure, with held-out sets and contamination controls, so results are trustworthy

  • Read eval signal and training curves to determine whether a change actually helped, and feed findings back to the research and environment teams

  • Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics

  • Implement methods from recent ML papers quickly and turn them into production-grade systems

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