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Bioinformatics Machine Learning Internship Jobs in Atlanta, GA

Coca-Cola

Senior Machine Learning Engineer (MLOPS)

Atlanta, GA · On-site

$100K - $138K/yr

... internship experience) inMLOps, Data Engineering, Software Engineering, or a related field. * 3+ ... A solid understanding of the machine learning lifecycle, containerized microservices architectures ...

Tata Consultancy Services

Agentic AI Engineer

Atlanta, GA · On-site

$110K - $132K/yr

... or internship experience in machine learning, AI, or data-driven projects. • Solid understanding of algorithms, data structures, and machine learning concepts. • Experience with data ...

Tata Consultancy Services

Agentic AI Engineer

Atlanta, GA

$110K - $132K/yr

... or internship experience in machine learning, AI, or data-driven projects. • Solid understanding of algorithms, data structures, and machine learning concepts. • Experience with data ...

Revenue Analytics

Data Scientist

Atlanta, GA · On-site

$95K - $110K/yr

What You Will Bring: * 0-2 years of experience in data science, analytics, machine learning, or a related field, including internships, research, senior projects, or meaningful independent projects.

Fisec Global

Gen AI Engineer

Atlanta, GA · On-site

Deploy machine learning models and ensure their effective integration into existing systems ... Experience mentoring junior colleagues and interns.

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Bioinformatics Machine Learning Internship information

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$24.5K

$41K

$84.6K

How much do bioinformatics machine learning internship jobs pay per year?

As of Sep 12, 2026, the average yearly pay for bioinformatics machine learning internship in Atlanta, GA is $40,951.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,300.00 and $44,200.00 per year, depending on experience, location, and employer.

What is a bioinformatics machine learning internship?

A Bioinformatics Machine Learning Internship is a temporary position, usually for students or recent graduates, where interns gain hands-on experience applying machine learning techniques to biological data. Interns may work on projects like analyzing genomic sequences, predicting protein structure, or developing algorithms for biomedical research. The role involves coding, data analysis, and collaborating with scientists to solve real-world biological problems. It offers exposure to both computational methods and biological sciences, preparing interns for careers in bioinformatics, data science, or research.

What are some typical projects or tasks a bioinformatics machine learning intern might work on during their internship?

As a Bioinformatics Machine Learning Intern, you'll often contribute to projects that involve developing and testing algorithms for analyzing biological data, such as genomic sequences or protein structures. Typical tasks may include preprocessing large datasets, implementing machine learning models to identify patterns or make predictions, and visualizing results for team discussions. Interns frequently collaborate with both computational scientists and experimental biologists, gaining exposure to interdisciplinary teamwork and real-world applications. This hands-on experience helps interns build both technical and domain-specific skills, preparing them for advanced roles in bioinformatics or data science.

What are the key skills and qualifications needed to thrive as a bioinformatics machine learning intern, and why are they important?

To thrive as a Bioinformatics Machine Learning Intern, you need a solid background in biology, statistics, and computer science, typically supported by relevant coursework or a degree in bioinformatics, computational biology, or a related field. Familiarity with programming languages like Python or R, experience using bioinformatics tools (e.g., BLAST, Bioconductor), and knowledge of machine learning frameworks such as TensorFlow or scikit-learn are highly valued. Attention to detail, problem-solving skills, and effective communication help interns collaborate on interdisciplinary teams and interpret complex datasets. These skills ensure interns can contribute meaningfully to research projects, derive insights from biological data, and communicate findings clearly.

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

AspectBioinformatics Machine Learning InternshipBioinformatics Data Analyst Internship
Required SkillsProgramming, machine learning, bioinformatics toolsData analysis, statistical skills, bioinformatics tools
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch labs, healthcare, biotech firms
Industry UsageDeveloping algorithms, predictive models in bioinformaticsAnalyzing biological data, generating reports

While both internships involve bioinformatics, the Bioinformatics Machine Learning Internship focuses on developing machine learning models and algorithms, whereas the Bioinformatics Data Analyst Internship emphasizes analyzing biological data and generating insights. Both roles require programming and bioinformatics skills but differ in their core focus and application.

What are popular job titles related to Bioinformatics Machine Learning Internship jobs in Atlanta, GA?

For Bioinformatics Machine Learning Internship jobs in Atlanta, GA, the most frequently searched job titles are:

What job categories do people searching Bioinformatics Machine Learning Internship jobs in Atlanta, GA look for?

The top searched job categories for Bioinformatics Machine Learning Internship jobs in Atlanta, GA are:

What cities near Atlanta, GA are hiring for Bioinformatics Machine Learning Internship jobs?

Cities near Atlanta, GA with the most Bioinformatics Machine Learning Internship job openings:

Bioinformatics Machine Learning Internship jobs near you
Infographic showing various Bioinformatics Machine Learning Internship job openings in Atlanta, GA as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 75% Full Time, 20% Part Time, and 3% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $40,951 per year, or $19.7 per hour.

Senior Machine Learning Engineer (MLOPS)

Atlanta, GA • On-site

The Coca-Cola Company
Food Services and Drinking Places • 10K+ employees
Learn more about The Coca-Cola Companyexternal

$100K - $138K/yr

Other

Posted 18 days ago

Coca-Cola rating

7.5

Company rating: 7.5 out of 10

Based on 445 frontline employees who took The Breakroom Quiz

Job description

The Coca-Cola Company's Technology organization isin the midst ofa digital transformation that allows our employees to use world class technology to connect our products to our customers all over the world. This journey is a very exciting time forCoca-Colaand our employees are big contributors to our Success and Growth. Our large scale and complex environmentoffersan incredible opportunity to address challenges, enable innovative solutions to make a difference for our customers.
In this position, you will embark on a journey of leveraging vast amounts of data to transform it into actionable insights. You will aid in the development of analytics models and work under the guidance of seasoned data science professionals to drive decision-making and strategyacross the organization. This is an exciting opportunity togrow in your career in data science and analytics within a supportive and innovative environment.
What You'll Do for Us:
  • Model Deployment & Operationalization: Partner with data science teams to transition machine learning models from experimentation to production environments, packaging models into robust Docker containers for scalable and reproducible deployments.

  • Pipeline Automation: Build and maintain automated CI/CD pipelines for machine learning workflows (e.g., model training, evaluation, and deployment) utilizing tools like GitHub Actions. Leverage Azure Container Registry to securely manage container images and deploy scalable workloads to Azure Kubernetes Service (AKS) or Azure Container Instances (ACS).

  • Utilize Azure Machine Learning and Microsoft Fabric Data Science to manage the ML lifecycle. Adapt prior experience from other cloud platforms to effectively navigate and optimize our current stack.

  • Monitoring & Maintenance: Implement monitoring solutions to track model performance, data drift, and system health in production. Ensure comprehensive logging and observability for containerized model endpoints running on Kubernetes clusters. Troubleshoot and resolve operational issues as they arise.

  • Data Integration: Collaborate with data engineering teams to ensure clean, reliable data pipelines (such as Medallion architectures) seamlessly feed into machine learning models.

  • Engineering Best Practices: Write clean, modular, and testable code (primarily in Python) while adhering to version control best practices using Git.

  • Mentor, guide, and develop junior/aspiringMLOpsEngineeracross the organization.

  • Lead continuous career development and drive engineering excellence through performance reviews.

Qualifications& Requirements:
  • 6+years of professional experience (or equivalent strong academic/internship experience) inMLOps, Data Engineering, Software Engineering, or a related field.

  • 3+ years of experience managing and scaling high-performingMLOpsor data platform teams, with a focus on career development, performance management, and technical mentorship.

  • Cloud ML Platforms: Hands-on experience with at least one major cloud ML platform. While Azure ML and Microsoft Fabric are preferred, experience with AWS SageMaker, Google Cloud Platform Vertex AI, or similar platforms is highly acceptable.

  • Programming: Strong proficiency in Python for scripting, automation, and model deployment.

  • DevOps & Containerization: Familiarity with version control (Git), building CI/CD pipelines (e.g., GitHub Actions, Azure DevOps), and containerization ecosystems (Docker, Azure Container Registry, Kubernetes/AKS/ACS).

  • Foundational Knowledge: A solid understanding of the machine learning lifecycle, containerized microservices architectures, and fundamental software engineering principles.

Functional Skills:
Practical experience with as many of the following as possible:
  • Handles multiple competing priorities in a fast-paced, deadline-driven environment

  • Strong attention to details and excellent problem-solving skills

  • Ability to work in a collaborative team environment

  • Highly innovative, adaptable, and self-directed

  • Results-oriented with a delivery focus

  • Presentation skills: Ability to communicate technical topics to business audience.

  • Be able to collaborate across other levels of the organization

  • Team player who can lead a discussion to defined outcomes

  • Effective Communication

  • Pursuing Innovation

What We Can Do for You:
  • Innovation & Technology:The ability to work with an award-winning team that is on the cutting edge of innovation.

  • Exposure to World Class Leaders:Availability to global technology leaders that will expand your network and exposure you to emerging technologies and techniques.

  • Agile Work Environment:We embrace agile with management that believes in removing barriers, so you are empowered to experiment, iterate and innovate.

Our Purpose and Growth Culture:
We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what's possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors - curious, empowered, inclusive and agile - and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class. When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws.

What Coca-Cola employees say

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Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Coca-Cola logo

About Coca-Cola

Sourced by ZipRecruiter

On May 8, 1886, Dr. John Pemberton brought his perfected syrup to Jacobs' Pharmacy in downtown Atlanta where the first glass of Coca‑Cola was poured. From that one iconic drink, we’ve evolved into a total beverage company. More than 2.2 billion servings of our drinks are enjoyed in more than 200 countries and territories each day. We are constantly transforming our portfolio, from reducing added sugar in our drinks to bringing innovative new products to market. We seek to positively impact people’s lives, communities and the planet through water replenishment, packaging recycling, sustainable sourcing practices and carbon emissions reductions across our value chain. Together with our bottling partners, we employ more than 700,000 people, helping bring economic opportunity to local communities worldwide. We are committed to offering people more of the drinks they want across a range of categories and sizes while driving sustainable solutions that build resilience into our business and create positive change for the planet.

Industry

Food services and drinking places and food and drink manufacturing

Company size

10,000+ Employees

Headquarters location

Atlanta, GA, US

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