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Machine Learning Engineer Jobs in Clemson, SC (NOW HIRING)

Varsity Tutors

Machine Learning Tutor

Greenville, SC · 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 ...

DISHER

Vision Engineer

Greenville, SC · Remote

Vision Engineer - Remote / Travel DISHER is currently partnering with a world leading automation ... Knowledge on machine learning with AI capabilities. * Self-driven and willingness to work long ...

DISHER

Vision Engineer

Greenville, SC · Remote

Vision Engineer - Remote / Travel DISHER is currently partnering with a world leading automation ... Knowledge on machine learning with AI capabilities. * Self-driven and willingness to work long ...

DISHER

Vision Engineer

Greenville, SC · Remote

Vision Engineer - Remote / Travel DISHER is currently partnering with a world leading automation ... Knowledge on machine learning with AI capabilities. * Self-driven and willingness to work long ...

Accenture

AI Architect, Manager

Greenville, SC · On-site +1

$59.25 - $78/hr

Understanding of data science and machine learning principles (Analytics) * DevOps, MLOps, SDLC, Agile Development * Azure AI Services (including Azure AI Foundry, Azure OpenAI, Azure Cognitive ...

Vertiv Co

Presales Structural Engineer

Pelzer, SC

At Vertiv, you'll work alongside a multidisciplinary team of engineering experts, leveraging and supporting emerging technologies such as AI, machine learning, and advanced data analytics to support ...

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Machine Learning Engineer information

See Clemson, SC salary details

$26.7K

$109.1K

$164K

How much do machine learning engineer jobs pay per year?

As of Jun 4, 2026, the average yearly pay for machine learning engineer in Clemson, SC is $109,105.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,000.00 and $131,300.00 per year, depending on experience, location, and employer.

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 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 jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.

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 Clemson, SC? The most popular types of Machine Learning Engineer jobs in Clemson, SC are:
What are popular job titles related to Machine Learning Engineer jobs in Clemson, SC? For Machine Learning Engineer jobs in Clemson, SC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Clemson, SC look for? The top searched job categories for Machine Learning Engineer jobs in Clemson, SC are:
What cities near Clemson, SC are hiring for Machine Learning Engineer jobs? Cities near Clemson, SC with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you

Machine Learning Engineer II

Techtronic Industries (TTI)

Anderson, SC • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 4 days ago

Techtronic Industries TTI rating

8.1

Company rating: 8.1 out of 10

Based on 34 frontline employees who took The Breakroom Quiz

119th of 416 rated machine equipment manufacturers

Job description

Job Description:
TTI Consumer Power Tools, Inc., has an opening in its Anderson, SC corporate office for a Electrical Machine Learning (ML) Engineer II that will report into the Sr. Director of Engineering. Come join the Engineering team at the most exciting and innovative tool company in the world!
Techtronic Industries is a fast-growing world leader in Power Tools, Accessories, Hand Tools, Outdoor Power Equipment, and Floor Care for Do-It-Yourself (DIY). The Company is committed to accelerating the transformation of these industries through superior environmentally friendly cordless technology. At TTI Anderson, our RYOBI brand is recognized worldwide for their deep heritage and cordless product platforms of superior quality, outstanding performance, safety, productivity, and compelling innovation.
Your Role On Our Team:
The Electrical ML Engineer II will identify, develop, and validate ML-enabled features for outdoor power tools within the OP EE organization. This role partners closely with cross-functional teams to translate customer needs into robust, data-driven solutions that can be demonstrated on-tool and matured toward production readiness.
Key responsibilities include framing ML use cases, designing data-collection strategies and ground-truth methods, performing data engineering and feature development, training and tuning models in Python, and executing disciplined validation to characterize accuracy, robustness, and corner cases. The engineer will also help establish and improve team workflows and guidelines covering the end-to-end ML lifecycle-from problem definition through model training, validation, and deployment considerations.
Primary Job Requirements:
  • Bachelor of Science degree in Computer Science, Computer Engineering, Electrical Engineering, or a related scientific/engineering discipline with completed coursework, certification, or specialization in Machine Learning, Data Science, or a closely related area.
  • Minimum 2 years of hands-on experience applying ML in an applied setting (e.g., embedded/edge, signal processing, sensing, or electromechanical products), including data collection and model validation.
  • Demonstrated experience applying fundamental ML approaches (e.g., supervised learning for classification/regression, feature engineering, model selection, and hyperparameter tuning).
  • Proficient in developing, debugging, and validating Python code, with experience in common libraries (NumPy, pandas, scikit-learn, Matplotlib, etc.).
  • Experience with modern software development practices and tools (Git-based workflows; familiarity with CI/CD and containers is a plus).
  • Ability to develop and debug code in an embedded environment (C/C++ preferred), including bring-up and hardware-facing troubleshooting will be a plus.
  • Basic knowledge of sensor technologies (e.g., IMUs, thermistors/temperature sensing, magnetic/optical sensing) and microcontroller interfacing.
  • Strong problem-solving and system-thinking skills, with the ability to work in a fast-paced, prototype-to-demo environment.
  • Strong technical communication skills and the ability to plan/execute work to meet project schedules.
  • Demonstrated ownership of deliverables, including understanding dependencies and collaborating effectively with cross-functional stakeholders.

We provide these great perks and benefits:
  • We offer competitive wages and a comprehensive benefits package
    • 401(k)
    • Medical/dental/vision coverage
    • Tuition assistance
    • Vacation and holidays.
  • On-site gym with a managing health and wellness professional.
  • In-house training and development staff.
  • Subsidized cafeteria and Starbucks coffee

What Techtronic Industries TTI employees say

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