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Junior Machine Learning Engineer Jobs in Charleston, SC

The Data Scientist leverages advanced analytics, statistical modeling, machine learning, and AI to ... Programming: Strong Python and SQL skills for building models and analyzing data, with hands-on ...

The Data Scientist leverages advanced analytics, statistical modeling, machine learning, and AI to ... Programming: Strong Python and SQL skills for building models and analyzing data, with hands-on ...

ENGINEER MANUFACTURING 4

Goose Creek, SC · On-site

$66K - $85K/yr

HII's diverse workforce includes skilled tradespeople; artificial intelligence, machine learning (AI/ML) experts; engineers; technologists; scientists; logistics experts; and business administration ...

ENGINEER MANUFACTURING 4

Goose Creek, SC

$66K - $85K/yr

HII's diverse workforce includes skilled tradespeople; artificial intelligence, machine learning (AI/ML) experts; engineers; technologists; scientists; logistics experts; and business administration ...

For those who want to keep growing, learning, and evolving. We at Kelly ® hear you, and we're here ... Programming, setting up, and operating a CNC Press Brake (preferably Amada), gantry style vertical ...

Showing results 41-60

Junior Machine Learning Engineer information

See Charleston, SC salary details

$31.4K

$67.2K

$102.5K

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

As of Aug 19, 2026, the average yearly pay for junior machine learning engineer in Charleston, SC is $67,191.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,400.00 and $74,900.00 per year, depending on experience, location, and employer.

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.

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 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 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.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn 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 are popular job titles related to Junior Machine Learning Engineer jobs in Charleston, SC?

For Junior Machine Learning Engineer jobs in Charleston, SC, the most frequently searched job titles are:

What job categories do people searching Junior Machine Learning Engineer jobs in Charleston, SC look for?

The top searched job categories for Junior Machine Learning Engineer jobs in Charleston, SC are:

What cities near Charleston, SC are hiring for Junior Machine Learning Engineer jobs?

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

Data Scientist

Maymont Homes

Charleston, SC • Remote

Full-time

Retirement, PTO

Re-posted 2 days ago


Job description

Location

Charleston - 997 Morrison Drive, Suite 402

Business

Our Growth, Your Opportunity

At Maymont Homes, our success starts with people, our residents and our team. We are transforming the single-family rental experience through innovation, quality, and genuine care. With more than 20,000 homes across 47+ markets, 25+ build-to-rent communities, and continued expansion on the horizon, we are more than a leader in the industry-we are a company that puts people and communities at the heart of everything we do.

As part of Brookfield, Maymont Homes is growing quickly and making a lasting impact. We are also proud to be Certified by Great Place to Work, a recognition based entirely on feedback from our employees. This honor reflects the culture of trust, collaboration, and belonging that makes Maymont a place where people thrive.

Join a purpose-driven team where your work creates opportunity, sparks innovation, and helps families across the country feel truly at home.

Job Description

**This position is onsite at 997 Morrison Dr, Charleston SC**

Primary Responsibilities: The Data Scientist leverages advanced analytics, statistical modeling, machine learning, and AI to solve complex business challenges and enable data-driven decision-making across the organization. This role develops, validates, and deploys predictive and statistical models using Python, while also performing hands-on data analysis, data extraction, and ad hoc reporting using Python, SQL, and Excel.

Working closely with cross-functional business partners, the Data Scientist translates business questions into analytical solutions, delivering actionable insights that support strategic initiatives and operational decision-making. The role is responsible for owning the end-to-end modeling lifecycle, including problem definition, data preparation, model development, validation, performance evaluation, and communication of results to both technical and non-technical audiences.

The ideal candidate combines strong expertise in data science, machine learning, and statistical analysis with practical proficiency in Python, SQL, and Excel. They are intellectually curious, analytical, and comfortable working with complex datasets to uncover meaningful insights. Success in this role requires the ability to quickly develop domain expertise in the housing industry, collaborate effectively with business stakeholders, and translate technical findings into clear, impactful recommendations that drive business value.

Skills & Competencies:

Qualifications:

  • Bachelor's degree in Data Science, Statistics, Economics, Finance, Applied Mathematics, Computer Science, Engineering, or a related quantitative field.

  • 3+ years of experience in data science, analytics, or applied quantitative work.

  • Strong problem-solving skills and attention to detail.

  • Strong Python, SQL, and Excel skills, with the ability to handle ad hoc data requests from business partners.

  • Excellent communication, collaboration, and presentation skills with both technical and business audiences.

  • Familiarity with Git, Agile development methodologies, and collaborative software development practices.

Preferred Qualifications:

  • Experience within real estate, private equity, investment management, asset management, or financial services.

  • Experience building and deploying predictive pricing, forecasting, or optimization models in production.

  • Experience utilizing geospatial analytics and external market data sources.

  • Experience with AWS cloud services and modern AI platforms.

Essential Skills:

  • Data Science & Machine Learning: Solid working knowledge of statistical modeling, predictive analytics, regression, and core machine learning methods, with hands-on experience building models.

  • Problem Solving: Ability to take a defined business problem, develop an analytical approach, and translate findings into clear, usable recommendations for business partners.

  • Excel & Ad Hoc Analysis: Advanced Excel skills, including the ability to quickly turn around ad hoc data requests, build clear analyses, and summarize results for business partners such as Asset Management and Operations.

  • Programming: Strong Python and SQL skills for building models and analyzing data, with hands-on experience using common libraries (e.g., pandas, scikit-learn).

  • Artificial Intelligence: Baseline experience working with AI tools, including an understanding of prompts and prompt engineering to improve analytical efficiency.

  • Model Deployment: Exposure to how models are deployed to production and monitored over time, with willingness to develop these skills alongside team members.

  • Collaboration: Ability to work effectively across data science, engineering, and business teams, building strong partnerships and contributing to shared goals.

  • Communication: Ability to clearly communicate complex analytical concepts to technical and non-technical audiences.

Essential Job Functions:

Typical Day Activities:

  • Partner with business teams, including Asset Management and Operations, to handle ad hoc data requests and support day-to-day operational and portfolio questions.

  • Build predictive models in Python to address defined business problems, such as pricing, occupancy, or operational performance, in collaboration with senior team members.

  • Help deploy models into production and monitor their performance, learning production best practices with support from senior team members and Data Engineering.

  • Summarize findings into clear, concise takeaways for business partners.

  • Collaborate with Data Engineering to ensure scalable, reliable, and trusted analytical datasets.

Key Metrics & Responsibilities:

  • Decision Support: Provide timely, accurate analysis and ad hoc data support that helps business partners make better decisions.

  • Model Building: Build and maintain models in Python that reliably address the business problems they are assigned to solve.

  • Quality of Analysis: Deliver accurate, well-organized analyses that business partners can trust and use.

  • Growth & Learning: Steadily expand technical skills and business knowledge, including new tools and modeling techniques and the housing industry, over time.

  • Data Quality & Analytical Standards: Ensure analytical rigor, statistical integrity, reproducibility, and documentation across all models and analyses.

Why work for Maymont Homes?

Our Mission - "We Positively Impact the Lives in the Communities We Serve." Every role contributes to this purpose, helping families find a place to call home while making a difference in the communities we support.

Certified Great Place to Work - Our people make us who we are. This certification celebrates the values and culture that fuel collaboration, innovation, and care.

Outstanding Benefits - Backed by Brookfield, our benefits include a 5% 401(k) match, wellness credits that reduce healthcare costs, and up to 160 hours of PTO annually for full-time employees.

Career Growth - With continued expansion planned for Maymont, you'll find meaningful opportunities to grow your skills, advance your career, and make an impact.

Strong Foundation - As part of Brookfield Asset Management, one of the world's largest real estate asset managers, we have the stability, resources, and vision to keep growing.

Equal Opportunity Employer: Minorities/Religion/Sex/Protected Veterans/Disability/Sexual Orientation/Gender Identity/Marital Status/Pregnancy/Age/National Origin/Genetic Information. #MYMT