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Mlops Engineer Internship Jobs (NOW HIRING)

Aerospace Corporation is hiring Machine Learning Engineering Interns for the Data Science and ... Familiarity with MLOps processes and tools (MLFlow, Data Version Control etc.) * Specific ...

New

Engineering Internship - Summer 2027

Saint Paul, MN · On-site

$17 - $22/hr

We are seeking candidates for internships in software engineering,data engineering,AI and machine ... MLOps,MLFlow) * Cloud - AWS (EC2, Serverless, Lambdas,EKS,Security,Sagemaker, Bedrock) * AI ...

New

Our Technology team is seeking exceptional college students for our Summer Internship Program ... Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools (ex: MLflow, Kubeblow) is a plus ...

Our Technology team is seeking exceptional college students for our Summer Internship Program ... Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools (ex: MLflow, Kubeblow) is a plus ...

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Mlops Engineer Internship information

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$11

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$29

How much do mlops engineer internship jobs pay per hour?

As of Sep 14, 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 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.

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 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 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.

More about Mlops Engineer Internship jobs

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Infographic showing various Mlops Engineer Internship job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 89% Full Time, 7% Part Time, and 3% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $40,174 per year, or $19.3 per hour.

2027 Machine Learning Engineering Graduate Intern

Full-time, Internship

Medical, Retirement, PTO

Posted 3 days ago

New


Job description

The Aerospace Corporation is the trusted partner to the nation's space programs, solving the hardest problems and providing unmatched technical expertise. As the operator of a federally funded research and development center (FFRDC), we are broadly engaged across all aspects of space- delivering innovative solutions that span satellite, launch, ground, and cyber systems for defense, civil and commercial customers. When you join our team, you'll be part of a special collection of problem solvers, thought leaders, and innovators. Join us and take your place in space.

Aerospace Corporation is hiring Machine Learning Engineering Interns for the Data Science and Artificial Intelligence Department (DSAID) within the Information Systems and Cyber Division (ISCD).

Information Systems and Cyber Division (ISCD) staff work with the latest in information system technologies, such as elastic compute clouds, containerization, microservices, real-time operating systems, and visualization frameworks, with expertise in cyber security, software architecture, software engineering, data science, Artificial Intelligence, process improvement, and software development to deliver responsive, resilient, high-performance software intensive systems to our Intelligence Community, DoD, and civilian customers.

DSAID consists of a diverse team of engineers, data scientists, and programmers with a passion for researching, prototyping, understanding, and building AI and data enabled tools across the space enterprise. We are a growing, innovative, and collaborative department providing technical expertise in AI and Machine Learning to many of Aerospace's customers, such as the Missile Defense Agency, NASA, Space Development Agency and the National Reconnaissance Office. We apply data science and AI knowledge across the space enterprise, to Aerospace enterprise capabilities, and towards corporate workforce development and strategic focus areas.

Machine Learning Engineers work on teams spanning various disciplines, experience levels, and organizational boundaries.

The selected candidate will be required to work full-time, onsite at our facility in El Segundo, CA, Chantilly, VA or Colorado Springs, CO.

What You'll Be Doing

  • Developing and executing machine learning and data science experiments, in the domains of natural language processing, computer vision, time series analysis, reinforcement learning, etc.
  • Evaluating technologies and data science models for use in scalable and resilient mission-critical applications
  • Collaborating with teams of various sizes to deliver features and products
  • Presenting written and verbal results to customer stakeholders.
  • Reinforcing an environment of learning and progress with team members and others

What Corporate Skills You'll Bring

  • Strong written and oral communication skills
  • Must work well in a team environment
  • Possess organizational, time management and project management skills
  • Demonstrate flexibility and ability to adapt to changing organizational need
  • Interpersonal skills to coordinate efforts and work with other internal and external organizations

What You Need to be Successful

Minimum Requirements

  • Currently enrolled full-time in an accredited college/university program pursuing a Master's or PhD degree in Computer Science, Computer Engineering, or related discipline.
  • Availability to work full-time for a minimum of 10 weeks outside of university term and ability to return to a Master's or PhD degree program full-time after completion of the internship.
  • Minimum GPA of 3.0
  • Bachelor's degree completed by internship start date
  • Proficiency in Python, including major ML libraries and tools (PyTorch)
  • Experience with container orchestration tooling (Docker, Kubernetes, etc.)
  • Experience with and understanding of machine learning and artificial intelligence, software engineering, and statistics
  • Experience with and understanding of software engineering concepts with an AI focus (MLOps/DevOps, ML Development Lifecycle, Scalable ML Architecture, etc.)
  • Familiarity with MLOps processes and tools (MLFlow, Data Version Control etc.)
  • Specific experience designing either computer vision or natural language processing applications leveraging ML models.
  • Experience in leveraging GPUs to scale and measure ML solution performance (NVIDIA developer tools etc.)
  • Familiarity with Unix/Linux operating systems
  • Experience with cloud native application development or cloud infrastructure, Microservice architectures
  • This position requires the ability to obtain and maintain a security clearance, which is issued by the U.S. government. U.S. citizenship is required to obtain a security clearance.
  • Transcripts required.

How You Can Stand Out

It would be impressive if you have one or more of these:

  • GPA 3.5 or higher
  • Active security clearance
  • Strong leadership skills
  • Familiarity with High Performance Computing hardware for ML (GPUs, TPUs), CUDA programming, and advanced ML optimization techniques and architectures
  • Experience with Slurm, Kubernetes or other cluster job orchestration frameworks leveraging GPU resources to run distributed ML training jobs at scale
  • Experience with building ML Solutions on edge and embedded hardware (ARM devices, Jetson Series, etc.)
  • Experience with Distributed and stream data processing, big data frameworks (Hadoop, Spark, Flink etc.)
  • Experience building scalable Agentic and Generative AI solutions for narrow-scoped use cases

Temporary housing assistance is not available.

We offer a competitive compensation package where you'll be rewarded based on your performance and recognized for the value you bring to our business. The grade-based pay range for this job is listed below. Individual salaries within that range are determined through a wide variety of factors including but not limited to education, experience, knowledge and skills.

(Min - Max) $32.00 - $38.00

Pay Basis: Hourly

Leadership Competencies

Our leadership philosophy is simple: every employee, regardless of level and role, can demonstrate leadership. At Aerospace, our commitment is our people. To cultivate our talent and ensure that we have a strong pipeline of future leaders, we want individuals who:

  • Operate Strategically
  • Lead Change
  • Engage with Impact
  • Foster Innovation
  • Deliver Results

Ways We Reward Our Employees

During your interview process, our team will provide details of our industry-leading benefits.

Benefits vary and are applicable based on Job Type. A few highlights include:

  • Comprehensive health care and wellness plans
  • Paid holidays, sick time, and vacation
  • Standard and alternate work schedules, including telework options
  • 401(k) Plan - Employees receive a total company-paid benefit of 8%, 10%, or 12% of eligible compensation based on years of service and matching contributions; employees are immediately eligible and vested in the plan upon hire
  • Flexible spending accounts
  • Variable pay program for exceptional contributions
  • Relocation assistance
  • Professional growth and development programs to help advance your career
  • Education assistance programs
  • An inclusive work environment built on teamwork, flexibility, and respect

We are all unique, from various backgrounds and all walks of life, yet one thing bonds all of us to each other-the belief that we can make a difference. This core belief empowers us to do our best work at The Aerospace Corporation.

Equal Opportunity Commitment

The Aerospace Corporation is an equal opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, age, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender, gender identity or expression, color, religion, genetic information, marital status, ancestry, national origin, protected veteran status, physical disability, medical condition, mental disability, or disability status and any other characteristic protected by state or federal law. If you're an individual with a disability or a disabled veteran who needs assistance using our online job search and application tools or need reasonable accommodation to complete the job application process, please contact us by phone at 310.336.5432 or by email at peoplemangmnt.mailbox@aero.org . You can also review Know Your Rights: Workplace Discrimination is Illegal .