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Machine Learning Engineer Intern Jobs in Lexington, SC

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Staff Forward Deployed Engineer

North, SC · On-site +1

$100K - $500K/yr

Applied Engineer, Machine Learning Engineer, MLOps Engineer, Platform Engineer, Infrastructure Engineer, Site Reliability Engineer, Field Application Engineer). * Experience turning ambiguous ...

CTIO AI Engineering Manager

Columbia, SC · On-site

$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 ...

AWS Generative AI Engineer

Columbia, SC · Hybrid

$60 - $78.75/hr

AWS Certified Machine Learning Engineer * AWS AI Practitioner * Experience with MLOps CICD and infrastructure as code tools Terraform CloudFormation * Familiarity with other LLM providers such as ...

NGA AI Engineer Manager

Columbia, SC · On-site

$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 ...

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 ...

We're looking for engineers fluent in modern AI application development - agent frameworks, harnesses, tool use, prompting, retrieval, and evaluation - not machine learning engineers. You will be ...

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 ...

Post Doctoral

Columbia, SC

$45K - $61K/yr

D.) degree in Chemical Engineering, Materials Science, Computational Chemistry, Chemical Physics, or a closely related field. Experience with molecular simulation, machine learning, or related ...

Software Developer (Columbia, SC) Design, develop, and maintain backend software systems and ... Integrate data enrichment processes and machine learning models into data processing workflows to ...

Post Doctoral

Columbia, SC · On-site

$45K - $61K/yr

D.) degree in Chemical Engineering, Materials Science, Computational Chemistry, Chemical Physics, or a closely related field. • Experience with molecular simulation, machine learning, or related ...

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Machine Learning Engineer Intern information

See Lexington, SC salary details

$21.8K

$36.5K

$75.3K

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

As of Aug 13, 2026, the average yearly pay for machine learning engineer intern in Lexington, SC is $36,450.00, according to ZipRecruiter salary data. Most workers in this role earn between $27,800.00 and $39,400.00 per year, depending on experience, location, and employer.

What do machine learning engineer interns do?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

What is a machine learning engineer intern?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

What skills and qualifications are needed to thrive as a machine learning engineer intern?

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

What are popular job titles related to Machine Learning Engineer Intern jobs in Lexington, SC? For Machine Learning Engineer Intern jobs in Lexington, SC, the most frequently searched job titles are:
What cities near Lexington, SC are hiring for Machine Learning Engineer Intern jobs? Cities near Lexington, SC with the most Machine Learning Engineer Intern job openings:
Infographic showing various Machine Learning Engineer Intern job openings in Lexington, SC as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $36,450 per year, or $17.5 per hour.

Senior AI/ML C++ software engineer

Recruiting Engine (MLS)

Lexington, SC

$104K - $138K/yr

Full-time

Re-posted 22 days ago


Job description

Senior Embedded Controls Engineer: C++/Linux and Machine Learning exp.
As an AI Machine Learning Engineer focus will be on designing and developing scalable solutions using AI tools and machine learning models. Addressing various neural network-related challenges in transportation sector. This involves leveraging big data computation and storage tools to create prototypes and datasets, conducting model training and evaluations, integrating solutions, performing bench tests and onsite tests, tuning, and monitoring. Proficiency in languages such as C and C++ is required, along with software development for Linux platforms.
Your responsibilities
Design and develop real time AI ? Neural Network solutions for transportation industry maintenance equipment. Implementing appropriate ML algorithms.
Write clean, documented code following best practices.
Develop and implement communication protocols.
Work independently and collaboratively with a motivated team.
Generate requirements and design documentation.
Plan for, design, and deliver testing, and tested products into the QA process.
Apply communication and problem-solving skills to solve software issues related to the design, development, deployment, testing, and operation of systems.
Qualifications
Education
Master"s / Bachelor"s degree in Software Engineering or similar experience.
Experience
5+ years of experience in developing CNN, R-CNN type neural network for computer vision tasks.
5+ years of experience in Software development using C++ & Linux embedded.
Experience with Supervised and Semi-Supervised Learning, Deep Learning, Support Vector Machines, Linear and Logistic Regression.
Working knowledge of AI Framework such as TensorFlow, Caf?, PyTorch, Keras, Darknet and OpenCV.
Working knowledge of AI edge devices such as NVIDIA Jetson / Nano / Orin.
Knowledge of the Linux Operating System.
Preferred Experience
Experience using statistical computer languages (R, Python, SQL etc.) to manipulate data and draw insights from large data sets.
Experience working with and creating data architectures.
Knowledge of a variety of machine learning techniques (semantic segmentation, clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.
Experience with edge computing & controlling devices (On-device deployment in C/C++ or similar) for real time application.
Experience with optimizing neural networks to perform well on low-power mobile platforms (e.g. pruning, distillation, quantization).