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

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

... engineering standards, and operational practices that enable safe, scalable adoption of artificial intelligence, generative AI, machine learning, and AI agents across the enterprise and product ...

New

... AI, machine learning, and advanced data analytics to support next-level solutions. You'll ... Bachelor's or equivalent degree in Electrical Engineering * Proficient in Electrical power system ...

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

The Prototype Machinist is an entry-level position responsible for learning and developing ... machine shop equipment, interpreting engineering drawings, performing basic machining operations ...

Production Engineer (Controls or Mechanical)

Piedmont, SC · On-site

$76K - $98K/yr

As the facility in Greenville, SC expands with seven new machine lines and two new assembly lines ... learning and career growth. What They Offer: Full Medical, Dental, and Vision Benefits on Day 1. ...

Experience or relevant project-based learning in gas turbine design, repair, manufacturing, or ... Machining. * Laser Applications. * Joining/Brazing. * Coating. * Inspection Technologies.

... data science, engineering, and advanced mathematics. * Conceptual Teaching & Problem-Solving ... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction:

Post Doctoral Fellow

Clemson, SC · On-site

$41K - $56K/yr

... machine learning techniques and ability to manage/analyze data and interpret the results. • ... programming tools (e.g., R, Python) applied to health or population-based research. • Project ...

Showing results 21-40

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 Sep 14, 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 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.

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 cities near Clemson, SC are hiring for Machine Learning Engineer jobs?

Cities near Clemson, SC with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Clemson, SC as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $109,105 per year, or $52.5 per hour.

Stream Restoration Engineer

Greenville, SC • On-site, Remote

Geosyntec Consultants, Inc.
Environmental Quality Programs Administration • 1 - 5K employees

Full-time

Posted 3 days ago

New


Job description

Overview

Are you seeking an opportunity to improve the world around you through stewardship of precious natural resources?

We are looking for a mid-career Stream Restoration Engineer to be in one of our following offices: Charlotte, NC; Raleigh, NC; Asheville, NC; Greenville, SC; Johnson City, TN. This opportunity offers a Hybrid work schedule within one of the offices listed. Typical work efforts include planning, design and construction assistance services on various projects including ecosystem restoration, urban stream/wetland improvement, mitigation banking, riverine engineering, stormwater engineering, coastal resiliency, along with associated environmental permitting and compliance. 

Geosyntec is an innovative, international engineering and consulting firm serving private and public-sector clients to address new ventures and complex problems involving our environment, natural resources, and civil infrastructure. Our engineers, scientists, technical and project employees serve our clients from offices across the world. Consistently ranked by ENR as one of the top environmental engineering design firms, Geosyntec is internationally known for its technical leadership, breadth of expertise, and exceptional client service. 

We invest in our people.  Each employee is unique, and your career at Geosyntec will be too.  We offer competitive pay and benefits, and well-being programs to support you and your family.

To Learn More Visit: http://www.geosyntec.com/careers/.

Essential Duties and Responsibilities
  • Directing multi-disciplinary project teams;
  • Performing and overseeing detailed fluvial geomorphic, sediment transport, biological, soil science, hydrologic and hydraulic studies;
  • Applying knowledge of CWA mitigation regulations and standard operation procedures (SOPs) for the establishment of stream and wetland mitigation banks within the U.S. Army Corps of Engineers Savannah, Mobile, Charleston, Wilmington, and Nashville Districts;
  • Leading and conducting field investigations and providing construction support services;
  • Developing construction documents, including engineering drawings and technical specifications;
  • Applying and/or directing innovative hydrologic and hydraulic modeling software, from 1-D to 3-D hydrologic, sediment transport and/or morphodynamic models;
  • Interacting with client representatives;
  • Project-level responsibility for scoping, performing, managing and delivering multiple concurrent project assignments;
  • Consistent with our sell-manage-do business model, play a role supporting lead generation, business development, staff development, and mentoring; and
  • Help broaden our reputation via publishing and visibility at prominent industry conferences.
  • Drive personal, company, and rental vehicles to client or company project or office sites, and other business locations, as needed.
Education and Licensure
  • Bachelor's degree in civil, agricultural, biological, or biosystem engineering, natural resources science, hydrotechnical, with emphasis on water resources or closely related discipline. (required)
  • Advanced degree in geology, natural resources science, environmental or civil engineering, with emphasis on water resources or closely related discipline. (preferred)
  • Ability to obtain Professional registration (within 3 years) if not presently held (i.e., P.E., P.G., P.W.S., A.E., C.E., CERP, CPSS and/or CPSC). (preferred)
Skills, Experience and Qualifications
  • At least 5 years (7+ years preferred) of consulting experience in fluvial geomorphology, ecological restoration (riverine/wetland/riparian systems), soil science, biological monitoring, mitigation banking, and natural resources remote sensing; or equivalent combination of education and experience. (required) 
  • Experience planning, conducting field and desktop data collection, data analysis, and application in an engineering context to restore degraded stream/riverine and wetland systems (e.g., developing engineering plans for construction execution). (required)
  • Experience producing Mitigation Plans and/or Mitigation Banking Instrument documents, including related agency (USACE) coordination.(preferred)
  • Significant experience with conducting fluvial geomorphologic assessments in streams and riverine systems (including the various methodologies that can be employed) and using remote sensing GIS toolsets for related analysis. (preferred)
  • Experience with remote sensing/modeling/design tools such as ArcGIS Pro, ArcGIS Hydro, coding in Python (or other code languages), HEC-RAS (1D & 2D), groundwater flow (riparian zones) models, HydroCAD and AutoCAD Civil 3D.  (preferred)
  • Experience with a variety of unmanned aerial systems (UAS) for geospatial data collection (e.g., LIDAR, imagery, etc.) and possessing an FAA remote pilot license (Part 107) or willingness to attain and maintain license. (preferred)
  • Experience with the application of the theory of machine learning and/or artificial intelligence (AI) methods to natural resource data analysis and solution generation. (preferred)
  • Strong oral and technical writing skills. (required)
  • Valid U.S. driver's license and a satisfactory driving record for business travel. (required)

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Employment Type: FULL_TIME