The Infosys MLOps Engineer Internship 2026 provides students with practical exposure to machine learning operations, model deployment, Python, cloud platforms, automation, Docker, Kubernetes, and machine learning workflows.
Infosys MLOps Engineer Interns may work with machine learning engineers, data scientists, software developers, DevOps engineers, cloud professionals, and data engineers.
According to the Stack Overflow Developer Survey 2025, Python was used by 57.9% of all respondents, making it one of the most widely used programming languages in the developer community.
Python is also commonly used across machine learning and MLOps workflows, making programming skills valuable for aspiring MLOps professionals.
Interns can strengthen their knowledge of Python, machine learning workflows, Docker, Kubernetes, Git, CI/CD, cloud platforms, APIs, model monitoring, and automation.
About Infosys MLOps Engineer Internship
Infosys is a global technology services and consulting company working across software engineering, artificial intelligence, cloud computing, cybersecurity, data, and digital transformation.
Infosys reported 3,28,594 employees globally in FY2026 and revenue of ?1,78,650 crore.
Its technology teams work across AI solutions, cloud platforms, software engineering, data services, digital platforms, and enterprise technology.
The company has technology centres and delivery teams across India and international markets.
Its technology ecosystem includes cloud and AI initiatives, application modernisation, automation, and digital engineering services.
Eligibility
Candidates applying for the Infosys MLOps Engineer Internship 2026 may need to meet requirements such as:
- Pursuing a bachelor’s, master’s, or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Information Technology, or a related field.
- Understanding Python programming.
- Familiarity with machine learning fundamentals.
- Understanding basic software development concepts.
- Knowledge of Git and version control.
- Basic understanding of Docker and containerisation.
- Familiarity with CI/CD concepts.
- Understanding of cloud computing fundamentals.
- Knowledge of Linux and command-line tools can be beneficial.
- Basic understanding of APIs and application integration.
- Familiarity with Kubernetes can be useful.
- Understanding of databases and data management.
- Basic knowledge of model deployment and monitoring.
- Familiarity with MLflow or similar tools can be an advantage.
- Strong analytical and problem-solving skills.
- Good written and verbal communication skills.
- Ability to collaborate with data scientists, developers, DevOps engineers, and cloud teams.
Roles & Responsibilities
An MLOps Engineer Intern at Infosys may be responsible for:
- Supporting machine learning model deployment.
- Assisting with machine learning pipelines.
- Writing and testing Python scripts.
- Working with Docker and containerised applications.
- Supporting CI/CD workflows for machine learning projects.
- Managing code through Git.
- Assisting with cloud-based ML infrastructure.
- Supporting model testing and validation.
- Monitoring deployed machine learning models.
- Identifying technical and deployment issues.
- Working with APIs and application integrations.
- Supporting automation of ML workflows.
- Assisting with Kubernetes-based deployments where required.
- Preparing technical documentation.
- Participating in code and workflow reviews.
- Collaborating with data scientists and software engineers.
- Reporting project progress to supervisors.
Application Process
Candidates interested in the Infosys MLOps Engineer Internship 2026 can follow these steps:
- Visit the official Infosys Careers website and search for MLOps Engineer internship opportunities.
- Review the job description and check the educational qualifications, machine learning skills, cloud requirements, location, duration, and eligibility criteria.
- Prepare a resume highlighting Python, machine learning, MLOps, Docker, cloud platforms, Git, and relevant projects.
- Include machine learning deployment projects, GitHub repositories, technical portfolios, or relevant project links where available.
- Add machine learning, cloud, DevOps, or MLOps certifications and relevant technical courses.
- Submit the application and provide the requested information and documents.
- Shortlisted candidates may be invited for coding assessments, machine learning assignments, MLOps tasks, or interviews.
- Interviews may cover Python, machine learning, Docker, CI/CD, cloud platforms, model deployment, monitoring, and project experience.
Selection Process
The Infosys MLOps Engineer Internship selection process may include:
- Application Screening: Academic qualifications, programming skills, machine learning knowledge, projects, certifications, and overall profile may be assessed.
- Technical Assessment: Candidates may be tested on Python, machine learning concepts, cloud computing, logical reasoning, and problem-solving.
- Technical Interviews: Questions may cover MLOps, model deployment, Docker, Kubernetes, CI/CD, cloud platforms, and machine learning workflows.
- Project Discussion: Candidates may explain their machine learning projects, deployment methods, tools, and technical contributions.
- Practical Task: Applicants may be given a coding, deployment, pipeline, or model monitoring assignment.
- Behavioural Interviews: Communication, teamwork, adaptability, analytical thinking, and problem-solving may be evaluated.
- Final Selection: Candidates who successfully complete the required stages may receive an internship offer and proceed with onboarding.
Benefits & Perks
Infosys MLOps Engineer Interns may receive:
- Compensation, depending on the position and location.
- Practical exposure to machine learning operations.
- Experience with model deployment and monitoring.
- Guidance from machine learning and cloud professionals.
- Exposure to Python and ML development workflows.
- Experience with Docker and containerisation.
- Familiarity with CI/CD and automation tools.
- Exposure to cloud-based machine learning platforms.
- Opportunities to strengthen programming and troubleshooting skills.
- Experience with machine learning pipelines.
- Professional development through project-based learning.
- Exposure to a global technology and consulting environment.
FAQs
The Infosys MLOps Engineer Internship may include compensation depending on the position and location. Candidates should check the specific internship posting for details.
The Infosys MLOps Engineer Internship does not have any one fixed annual application date. Openings may depend on project requirements and business needs.
Final-year students may apply for the Infosys MLOps Engineer Internship if they meet the education and other requirements mentioned in the relevant job posting.
Completing the Infosys MLOps Engineer Internship does not guarantee a pre-placement offer. Future employment depends on performance and business requirements.
After submitting an Infosys MLOps Engineer Internship application, Infosys may review the candidate's profile. Shortlisted candidates may be contacted for assessments, technical assignments, or interviews.
Candidates may apply for another Infosys MLOps Engineer Internship opening if they meet its eligibility requirements. Each new job posting should be reviewed before applying.
Eligibility for the Infosys MLOps Engineer Internship depends on the individual job posting. Students from relevant technical fields with Python, machine learning, cloud, and DevOps skills may apply.
The Infosys MLOps Engineer Internship may require Python, machine learning, Docker, Git, CI/CD, cloud computing, model deployment, monitoring, and problem-solving skills. Some roles may also prefer Kubernetes, MLflow, or cloud ML platform knowledge.
Candidates should start checking Infosys MLOps Engineer Internship 2026 openings several months before their preferred internship period.
There is no single deadline for every Infosys MLOps Engineer Internship 2026 position. Candidates should check the deadline mentioned in the individual job posting.
There is no universal GPA requirement for every Infosys MLOps Engineer Internship position. Academic requirements may vary by role.
Beware of Scammers
