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Mlops Engineer Internship Jobs (NOW HIRING)

Associate Data Engineer (AI/ML)

Plano, TX · On-site

$56K - $56K/yr

... internships, research, or personal projects. Exposure to machine learning frameworks, cloud ... technologies, MLOps practices, and production-quality development standards. Duties and ...

Internship, research, or project experience applying ML to real-world or research datasets ... Exposure to MLOps concepts such as experiment tracking or model versioning * Coursework or project ...

Up to 2 years of practical experience (internships, co-ops, or substantial academic/personal ... Exposure to deep learning frameworks (PyTorch, TensorFlow), MLOps/observability (MLflow ...

Up to 2 years of practical experience (internships, co-ops, or substantial academic/personal ... Exposure to deep learning frameworks (PyTorch, TensorFlow), MLOps/observability (MLflow ...

$104K - $142K/yr

... internships, bootcamps, or self‑directed learning. 3+ years of experience in AI/ML, data ... Experiences/Education - Desired Experience applying DevOps and MLOps practices to AI systems ...

ML Infrastructure Engineer, Fauna

New York, NY · On-site

$117K - $154K/yr

... Build and maintain MLOps infrastructure: experiment tracking, model versioning, evaluation ... BASIC QUALIFICATIONS - 5+ years of non-internship professional software development experience - 5+ ...

Exposure to cloud environments (AWS, GCP, or Azure) through coursework, internships, or personal projects. * Eagerness to learn and apply best practices in data engineering and MLOps. * Passionate ...

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Mlops Engineer Internship information

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How much do mlops engineer internship jobs pay per hour?

As of Jun 23, 2026, the average hourly pay for mlops engineer internship in the United States is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $20.91 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an MLOps Engineer Intern, and why are they important?

To thrive as an MLOps Engineer Intern, a strong foundation in machine learning concepts, programming (Python, Bash), and familiarity with cloud platforms is essential, often backed by studies in computer science or a related field. Experience with tools such as Docker, Kubernetes, CI/CD pipelines, and version control systems like Git is typically required. Strong problem-solving skills, collaboration, and adaptability help interns navigate technical challenges and team environments. These skills and qualities are crucial for efficiently deploying, maintaining, and scaling machine learning models in production settings.

What are some typical projects or tasks I might work on during an MLOps Engineer Internship?

As an MLOps Engineer Intern, you can expect to work on tasks such as automating machine learning model deployment pipelines, setting up continuous integration/continuous deployment (CI/CD) workflows, and monitoring models in production. You may also assist with optimizing infrastructure for machine learning workloads, ensuring reproducibility of experiments, and collaborating closely with data scientists and software engineers. These projects are designed to give you hands-on experience with real-world MLOps tools and practices, preparing you for a full-time role in the field.

What is the difference between Mlops Engineer Internship vs Data Engineer Internship?

AspectMlops Engineer InternshipData Engineer Internship
Required CredentialsBasic knowledge of machine learning, cloud platforms, scriptingStrong SQL, programming, data modeling skills
Work EnvironmentTech companies, startups, cloud service providersData-centric teams, analytics firms, tech companies
Industry UsageAI/ML projects, deployment pipelinesData pipelines, database management
Search & Comparison IntentUnderstanding roles in ML deploymentUnderstanding data infrastructure roles

The comparison between Mlops Engineer Internship and Data Engineer Internship highlights that both roles involve working with data and cloud technologies but focus on different aspects. Mlops internships emphasize deploying and maintaining machine learning models, while Data Engineer internships focus on building data pipelines and infrastructure. Candidates should choose based on their interest in ML deployment versus data management.

What is an MLOps Engineer Internship?

An MLOps Engineer Internship is a temporary position designed for students or recent graduates to gain hands-on experience in the field of Machine Learning Operations (MLOps). Interns typically work alongside experienced engineers to help streamline and automate the process of deploying, monitoring, and maintaining machine learning models in production environments. The internship provides valuable exposure to tools and practices such as CI/CD for ML, containerization, model versioning, and cloud platforms. This role is ideal for those looking to bridge the gap between data science and software engineering, gaining practical skills in both areas. Interns often contribute to real-world projects and learn about best practices in scaling and operationalizing AI solutions.
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Agentic AI/ Edge Computing SW Engineer

Agentic AI/ Edge Computing SW Engineer

Zebra Technologies

Holtsville, NY • Hybrid

Full-time

Medical, PTO

Posted 7 days ago


Zebra Technologies rating

7.4

Company rating: 7.4 out of 10

Based on 27 frontline employees who took The Breakroom Quiz

79th of 139 rated electronics manufacturers


Job description

Overview:

At Zebra, we are a community of innovators who come together to create new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer's and partner's needs and solve their challenges.

Being part of Zebra Nation means you are seen, heard, valued, and respected. Drawing from our unique perspectives, we collaborate to deliver on our purpose. Here you are part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve.

You'll have opportunities to learn and lead in a forward-thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about-locally and globally.

Come make an impact every day at Zebra.

What We're Looking For:

As the Agentic AI/ Edge Computing SW Engineer, you will help build the next generation of intelligent systems that bridge our hardware products with sophisticated backend AI processing. You will be responsible for creating and implementing robust AI-powered workflows that process real-time data from a variety of distributed endpoints. This involves designing and developing solutions that are scalable, efficient, and capable of delivering actionable insights within complex enterprise environments.
This role is a critical part of our broader initiative to revolutionize our engineering organization by leveraging autonomous and semi-autonomous AI agents. You will apply rigorous software engineering principles to transform AI innovations into practical, reliable, and performant solutions that will redefine productivity and accelerate new product development across Zebra.
This role is a hybrid position and requires a minimum of three days per week in Holtsville, NY Office. Zebra reserves the right to modify your work location based on business need.
  • Design, develop, and test a variety of AI-driven software assignments as part of a larger project.
  • Contribute to the implementation of production-grade AI agent systems, from single-purpose agents to more complex frameworks.
  • Develop and maintain AI-powered applications on Android platforms, including creating data pipelines to on-premises servers for AI processing.
  • Implement and maintain data pipelines between mobile devices and AI servers, leveraging knowledge of networking technologies.
  • Collaborate with senior engineers to develop and integrate AI agents into our New Product Development playbooks.
  • Participate in project code reviews and provide input on software design.
  • Implement AI model pipelines, including data preprocessing and inference, into software systems.
  • Conduct rigorous testing of AI models and software to ensure reliability, accuracy, and compliance with requirements; review test results and perform root cause analysis to identify problems.
  • Make changes or upgrades to existing software, enhancing and improving existing technologies to apply to new solutions.
  • Create and maintain technical documentation for software, APIs, and system components.
  • Stay up to date with the latest AI and software development tools, frameworks, and technologies to drive innovation.

Minimum Qualifications:

  • Bachelor's degree in Computer Science, Engineering, or a related discipline.
  • 2+ years of professional software development experience, or a Master's degree with relevant project/internship experience.
  • At least 1 year of practical exposure to AI/ML systems, frameworks, or AI-enabled applications (can be through projects, internships, or professional work).
  • Proficiency in Python and experience with modern AI frameworks and libraries (e.g., LlamaIndex, LangChain, OpenAI APIs, TensorFlow/PyTorch, Hugging Face).
  • Experience with Docker Containers and Kubernetes
  • Understanding of networking concepts and data transfer protocols (e.g., REST APIs).
  • Familiarity with AI agent concepts such as planning, tool use, and reasoning.
  • Solid software engineering fundamentals, including data structures, algorithms, and version control (Git).

Preferred Qualifications:

  • Master's degree in a relevant field.
  • Experience with or knowledge of Android application development.
  • Knowledge or previous projects in training and fine tuning AI models is highly desired.
  • Knowledge of Retrieval-Augmented Generation (RAG) and its integration with vector databases.
  • Experience with MLOps and deploying AI/ML models in a cloud environment (e.g., AWS, GCP, Azure).
  • Exposure to Nvidia CUDA toolkit.
  • Familiarity with Agent Development Kits (ADK).
  • Experience building or contributing to multi-agent systems.
  • Experience integrating AI solutions with enterprise tools and APIs.

Key Skills and Competencies

  • A pragmatic, "builder" mindset with a passion for prototyping and iterative development.
  • Excellent problem-solving skills and an eagerness to tackle complex challenges.
  • Good understanding of software engineering principles (e.g., system design, CI/CD).
  • Strong collaboration and communication skills.
  • Curiosity and a drive to learn new technologies.

Equal Opportunity Employer:

Zebra is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability and protected veteran status, or any other basis prohibited by law. If you are an individual with a disability and need assistance in applying for a position, please contact us at workplace.accommodations@zebra.com.

Know Your Rights:

https://www.eeoc.gov/sites/default/files/2022-10/EEOC_KnowYourRights_screen_reader_10_20.pdf

Conozca sus Derechos:

https://www.eeoc.gov/sites/default/files/2022-10/22-088_EEOC_KnowYourRightsSp_10_20.pdf

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation at workplace.accommodations@zebra.com .

Pay Range:

$86,080.00 - $129,120.00 Annual

Incentive Compensation:

In addition to base pay, Zebra offers this role the opportunity to earn a performance-based annual cash incentive, at a target equal to 10% of base pay, in accordance with the terms of the applicable incentive plan.

Zebra Total Rewards:

Zebra Total Rewards includes more than just pay and is structured to meet the needs of our changing global business and evolving talent. We are committed to providing our employees with a benefits program that is comprehensive and competitive - including healthcare, wellness, inclusion networks, and continued learning and development offerings. We offer community service days, in addition to the traditional insurances, compensation, parental leave, employee assistance program and paid time off offerings depending on the country where you work.

Salary offered will vary depending on your location, job-related skills, knowledge, and experience.

Additionally, all Zebra roles are eligible for cash incentive programs. For example, sales roles have additional opportunity to earn substantial variable compensation tied to quota achievement. In most other roles, the Zebra annual cash incentive program links Company and individual performance together. Some roles may also be eligible for long-term incentive equity awards.

Benefits:

We understand the importance of work-life balance and wellbeing, which is why we offer flexibility for our teams including: hybrid work, adaptable hours, Summer Flex Fridays, Focus Fridays, and an annual companywide well-being day to promote revitalization and success.

Job Posting Statement:

To protect candidates from falling victim to online fraudulent activity involving fake job postings and employment offers, please be aware our recruiters will always connect with you via @zebra.com email accounts. Applications are only accepted through our applicant tracking system and only accept personal identifying information through that system. Our Talent Acquisition team will not ask for you to provide personal identifying information via e-mail or outside of the system. If you are a victim of identity theft contact your local police department.

AI Technology Statement:

Zebra Technologies leverages AI technology to evaluate job applications using objective, job-relevant criteria. This approach enhances efficiency and promotes fairness in the hiring process. However, every decision regarding interviews and hiring is made by our dedicated team, because we believe people make the best decisions about people. For more on how we use technology in hiring and how we process applicant data, see our Zebra Privacy Policy.


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