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Junior Machine Learning Engineer Jobs in Fort Mill, SC

1 point system

Machine Learning Engineer

Fort Mill, SC · Remote

$48/hr

Job Title Machine Learning Engineer Location Remote Rate $48/hr on W2 Must Haves: Neaural networks NLP Python AZURE Pytorch or tensorflow Machine Learning Engineer / AI Engineer Role Role Overview ...

New

The Hartford

Senior AI Machine Learning Engineer

Charlotte, NC · Hybrid

$119K - $157K/yr

As a Senior Machine Learning Engineer , you will play a critical role in designing, building, and ... Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable ...

Bespoke Labs

Machine Learning Engineer

Charlotte, NC · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Rock Hill, SC · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Tihinsurance

Machine Learning Engineer

Charlotte, NC

... 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 ...

New

The Hartford

Sr AI Machine Learning Engineer

Charlotte, NC · Hybrid

$117K - $175K/yr

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations ... Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable ...

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

Charlotte, NC · Remote

$18 - $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

Matthews, NC · Remote

$18 - $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 ...

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

Junior Machine Learning Engineer information

See Fort Mill, SC salary details

$29.4K

$63.1K

$96.2K

How much do junior machine learning engineer jobs pay per year?

As of Jul 29, 2026, the average yearly pay for junior machine learning engineer in Fort Mill, SC is $63,094.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,600.00 and $70,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Junior Machine Learning Engineer, and why are they important?

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What kinds of projects and responsibilities can a Junior Machine Learning Engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What is the difference between Junior Machine Learning Engineer vs Data Scientist?

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

What does a junior machine learning engineer do?

A junior machine learning engineer assists in developing, testing, and deploying machine learning models under supervision. They work with data preprocessing, feature engineering, and use tools like Python and libraries such as TensorFlow or scikit-learn to support AI projects. This role often requires foundational knowledge of algorithms, programming, and data analysis.

How much does a junior machine learning engineer make?

A junior machine learning engineer typically earns between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level often requires advanced degrees, specialized certifications, and a strong track record of impactful projects.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and programming with tools like Python and TensorFlow. These positions usually involve leadership, strategic planning, and significant experience, and they tend to be found in large tech companies or specialized AI firms.

What Does a Junior Machine Learning Engineer Do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

More about Junior 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 Junior Machine Learning Engineer jobs in Fort Mill, SC? For Junior Machine Learning Engineer jobs in Fort Mill, SC, the most frequently searched job titles are:
What job categories do people searching Junior Machine Learning Engineer jobs in Fort Mill, SC look for? The top searched job categories for Junior Machine Learning Engineer jobs in Fort Mill, SC are:
What cities near Fort Mill, SC are hiring for Junior Machine Learning Engineer jobs? Cities near Fort Mill, SC with the most Junior Machine Learning Engineer job openings:
Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Fort Mill, SC as of July 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $63,094 per year, or $30.3 per hour.

Machine Learning Engineer

1 point system

Fort Mill, SC • Remote

$48/hr

Contractor

Posted 2 days ago

New

Job description

Hi ,
I hope you're doing well.

I'm reaching out regarding an exciting opportunity that I believe aligns well with your background and skill set.

To move forward, could you please provide the following details along with latest copy of resume:

Work Authorization and Expiry (If any)

LinkedIn Profile URL

Current Location with Zip code

Pay Expectation on W2 (hourly)

Complete JD:

Job Title

Machine Learning Engineer

Location

Remote

Rate

$48/hr on W2

Must Haves:
Neaural networks
NLP
Python
AZURE
Pytorch or tensorflow
Job Description:
Machine Learning Engineer / AI Engineer Role

Role Overview

This role is focused on developing, deploying, and optimizing machine learning models for enterprise applications. The ideal candidate should have strong hands-on experience with machine learning algorithms, neural networks, NLP, Python/R/SQL, modern ML frameworks, Microsoft Azure, and DevOps/MLOps practices. This is not just a data science research role — the candidate needs to be able to build models and support deployment/management in a production environment.

Must-Have Skills

The candidate must have hands-on experience with:

  • Supervised and/or unsupervised machine learning algorithms
  • Neural networks
  • Natural Language Processing, NLP
  • Python
  • R
  • SQL
  • TensorFlow, Keras, and/or PyTorch
  • Microsoft Azure cloud platform
  • DevOps and/or MLOps practices
  • Model development, deployment, optimization, and lifecycle management

Strong Fit Profile

A strong candidate will have experience building and deploying machine learning models from end to end. They should be comfortable selecting the right algorithms, preparing and analyzing data, training models, evaluating performance, and deploying models into cloud-based environments.

They should also understand MLOps concepts such as CI/CD for ML models, version control, monitoring, automation, model retraining, and production support. Azure experience is important, especially if they have used Azure Machine Learning, Azure DevOps, Azure Databricks, Azure Functions, or related cloud services.

Key Screening Questions

Machine Learning Experience

  1. Can you walk me through a machine learning model you developed from start to finish?
  2. What supervised learning algorithms have you worked with most often?
  3. What unsupervised learning algorithms have you used, and what business problems were they solving?
  4. How do you determine which algorithm is the best fit for a use case?
  5. How do you evaluate model performance and accuracy?

Neural Networks / NLP

  1. What experience do you have building or working with neural networks?
  2. Have you worked on any NLP-related projects? If so, what was the use case?
  3. What NLP techniques, libraries, or models have you used?
  4. Have you worked with text classification, sentiment analysis, entity extraction, chatbots, or language models?
  5. How do you clean and prepare text data for NLP models?

Tools / Programming Languages

  1. How strong would you rate your Python skills?
  2. Have you used R in a professional setting? If yes, for what type of work?
  3. How have you used SQL in your machine learning or data science work?
  4. Which ML frameworks have you used: TensorFlow, Keras, PyTorch?
  5. Which framework are you strongest in, and why?

Azure / Cloud Experience

  1. What Microsoft Azure services have you used for machine learning or data work?
  2. Have you used Azure Machine Learning before?
  3. Have you deployed ML models into Azure environments?
  4. Have you worked with Azure DevOps, Azure Databricks, Azure Functions, or Azure Pipelines?
  5. Can you describe a cloud-based ML project you supported?

DevOps / MLOps

  1. What does MLOps mean in your previous experience?
  2. Have you built or supported CI/CD pipelines for machine learning models?
  3. How have you handled model versioning, monitoring, or retraining?
  4. Have you worked with containerization tools like Docker or Kubernetes?
  5. How do you manage models once they are in production?

Deployment / Optimization

  1. Have you deployed machine learning models into production?
  2. What challenges have you faced during model deployment?
  3. How do you monitor model performance after deployment?
  4. Have you optimized models for performance, scalability, or accuracy?
  5. What steps do you take when a model’s performance starts to decline?

Candidate Must Be Able to Explain

The recruiter should listen for examples where the candidate can clearly explain:

  • What business problem they were solving
  • What data they used
  • What algorithm or model they selected
  • Why they selected that approach
  • What tools/frameworks they used
  • How they measured success
  • How the model was deployed
  • How the model was monitored or maintained
  • Their exact role in the project

Green Flags

Strong candidates may mention experience with:

  • Azure Machine Learning
  • Azure DevOps
  • Azure Databricks
  • CI/CD pipelines
  • Model monitoring
  • Model retraining
  • Model versioning
  • Feature engineering
  • NLP pipelines
  • Text classification
  • Neural network architecture
  • TensorFlow, Keras, or PyTorch in production
  • Python-heavy ML development
  • SQL for data extraction and analysis
  • End-to-end model deployment
  • Production ML environments
  • MLOps lifecycle ownership

Red Flags

Watch out for candidates who:

  • Only have academic or theoretical ML experience
  • Cannot explain specific models they have built
  • Have used Python only for scripting, not ML development
  • Have no Azure experience
  • Have no production deployment experience
  • Only know ML frameworks at a high level
  • Have no DevOps or MLOps exposure
  • Cannot explain supervised vs. unsupervised learning
  • Have only used pre-built tools without understanding the models
  • Cannot describe how they monitored or optimized a model after deployment

Quick Recruiter Intake Notes

Top priority: ML model development + deployment

Cloud requirement: Microsoft Azure

Programming must-haves: Python, R, SQL

Frameworks: TensorFlow, Keras, PyTorch

AI/ML focus: Supervised learning, unsupervised learning, neural networks, NLP

Operational focus: DevOps/MLOps, model deployment, monitoring, optimization

Best candidates: Hands-on ML engineers or data scientists with production deployment experience

Avoid: Candidates who only have academic ML exposure or no Azure/MLOps experience

Thank You

Ranjeet Kumar | 1Point System LLC

Senior Technical Recruiter
• Email: ranjeet@1pointsys.com • Fax: 803-832-7973 • www.1pointsys.com

https://www.linkedin.com/in/ranjeet-kumar-829a4525b/

If you are unable to reach me directly, please feel free to contact my supervisor at ashish.trivedi@1pointsys.com . They will be able to assist you with any inquiries or provide the support you need.


115 Stone Village Drive • Suite C • Fort Mill, SC • 29708

         An E-Verified company | An Equal Opportunity Employer