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Internship Graduate Machine Learning Jobs in Georgia

CNN

Machine Learning Engineer I

Atlanta, GA · On-site

Required : • Graduate degree (MS or PhD) in Computer Science, Mathematics, Statistics ... machine learning systems in production environments • Strong Python programming skills and ...

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Internship Graduate Machine Learning information

How much do ML interns get paid?

Machine Learning interns typically earn between $15 and $30 per hour, depending on the company, location, and level of experience. Internships often last 10 to 12 weeks and may include additional benefits such as mentorship and skill development opportunities.

What is the difference between Internship Graduate Machine Learning vs Data Analyst?

AspectInternship Graduate Machine LearningData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related field; basic knowledge of programming and statisticsDegree in Statistics, Mathematics, or related field; proficiency in data visualization and analysis tools
Work EnvironmentTech companies, research labs, startups; project-based, collaborative teamsBusiness, finance, marketing sectors; focus on reporting and data interpretation
Employer & Industry UsageUsed in tech, AI, and research industries for developing machine learning modelsCommon in corporate, finance, and consulting firms for data-driven decision making

While both roles involve working with data, an Internship Graduate Machine Learning focuses on developing algorithms and models using programming skills, often in tech environments. In contrast, a Data Analyst emphasizes interpreting data, creating reports, and supporting business decisions. The roles overlap in data handling but differ in technical depth and application focus.

What are the big 4 internships?

The big 4 internships typically refer to internship programs offered by the four largest professional services firms: Deloitte, PricewaterhouseCoopers (PwC), Ernst & Young (EY), and KPMG. These internships provide opportunities in areas such as audit, consulting, tax, and advisory services, often targeting students pursuing degrees in business, finance, or related fields. They are highly competitive and often include training, mentorship, and potential pathways to full-time employment.

What are the key skills and qualifications needed to thrive as an Internship Graduate in Machine Learning, and why are they important?

To thrive as an Internship Graduate in Machine Learning, you typically need a strong background in mathematics, programming (especially Python), and familiarity with algorithms and data structures, often supported by coursework or a degree in computer science, statistics, or a related field. Hands-on experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of tools such as Jupyter Notebooks and version control systems like Git, are highly valued. Curiosity, problem-solving, teamwork, and effective communication are crucial soft skills to excel in collaborative and innovative environments. These competencies enable interns to contribute to real-world projects, adapt to fast-changing technologies, and communicate findings clearly within interdisciplinary teams.

What are Internship Graduate Machine Learning positions?

Internship Graduate Machine Learning positions are entry-level roles designed for recent graduates or students who have completed coursework in machine learning, data science, or related fields. These internships provide hands-on experience working with real-world data, building and testing machine learning models, and collaborating with experienced professionals. Interns gain exposure to industry-standard tools and techniques, helping them bridge the gap between academic learning and practical application. Such positions are valuable for building a portfolio, networking, and enhancing job prospects in the rapidly growing field of artificial intelligence.

What types of projects do Internship Graduate Machine Learning roles typically involve, and how are responsibilities structured within the team?

Internship Graduate Machine Learning roles often focus on supporting ongoing research or development projects, such as building predictive models, cleaning and analyzing data, or prototyping algorithms. Interns usually collaborate closely with data scientists and engineers, contributing to specific project milestones while learning best practices in model development and deployment. Responsibilities are often structured to allow for mentorship and feedback, with interns participating in regular team meetings, code reviews, and brainstorming sessions. This collaborative environment provides valuable exposure to real-world machine learning workflows and helps interns build both technical and soft skills relevant to the field.

Which 5 jobs will survive AI?

Jobs that require complex human judgment, creativity, emotional intelligence, and specialized skills—such as healthcare professionals, data scientists, software developers, educators, and skilled tradespeople—are more likely to persist despite AI advancements. These roles often involve tasks that are difficult for AI to fully replicate or automate, especially when combined with continuous learning and adaptability.

Is PG in AI worth it?

A postgraduate degree in AI can enhance qualifications for machine learning internship roles by providing advanced knowledge of algorithms, data analysis, and programming skills. It may improve job prospects and salary potential but is not always mandatory, as practical experience and skills in tools like Python and TensorFlow are highly valued in the field.
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Internship Graduate Machine Learning jobs near you
Machine Learning Engineer I

Machine Learning Engineer I

CNN

Atlanta, GA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary:
CNN is a global leader in news and information, seeking a Machine Learning Engineer I to build and deploy ML systems that enhance personalization, search, recommendations, and content understanding for millions of users. The role involves collaborating with cross-functional teams and working on production ML systems that have measurable product impact.
Responsibilities:
• Build and deploy full-lifecycle machine learning systems in Python for CNN digital products, including personalization, search, recommendations, and content understanding
• Develop and maintain production ML pipelines, including feature engineering, model training, evaluation, and serving infrastructure
• Implement rigorous experimentation and A/B testing frameworks to validate model performance and product impact
• Optimize ML systems for real-time, web-scale performance serving millions of users
• Partner with platform and infrastructure teams to ensure ML systems meet reliability, scalability, and performance standards
• Contribute to code reviews, documentation, and team knowledge sharing
Qualifications:
Required:
• Graduate degree (MS or PhD) in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field
• 1+ years of professional experience building and deploying machine learning systems in production environments
• Strong Python programming skills and experience with machine learning frameworks (e.g., scikit-learn or similar)
• Experience across the full ML lifecycle, including data preprocessing, feature engineering, model training, evaluation, and deployment
• Solid understanding of software engineering best practices, including version control, testing, and CI/CD
• Ability to collaborate effectively with cross-functional partners
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders
Preferred:
• Experience working on large-scale consumer internet products (e.g., social, streaming, e-commerce, media)
• Hands-on experience with recommendation systems, search, NLP, or information retrieval
• Familiarity with data pipelines, feature stores, or embedding infrastructure
• Experience with experimentation platforms, A/B testing, and experimentation analysis
• Knowledge of cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes)
• Interest in generative AI applications and/or the media and news industry
Company:
CNN Worldwide is the most honored brand in cable news, reaching more individuals on television and online than any other cable news organization in the United States. Founded in 1980, the company is headquartered in Jakarta, IDN, with a team of 1001-5000 employees. The company is currently Late Stage.

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