Sony Research India Hiring 2026: Data Science Intern – Work From Home | 6-Month Paid Internship

Sony Research India is offering an exciting opportunity for students and aspiring researchers interested in artificial intelligence, machine learning, data science, and video analysis. The Sony Research India Data Science Intern Recruitment 2026 is aimed at technically strong candidates who want to work on advanced AI/ML algorithms, large-scale datasets, predictive models, and video analysis architectures.

According to the supplied LinkedIn job listing, the internship is remote within India and is scheduled to begin in the first week of November 2026. The internship is paid and runs for six months, giving selected candidates an opportunity to gain practical research and engineering experience while working on advanced technologies.

This opportunity may be particularly valuable for candidates with a strong foundation in Python, PyTorch, TensorFlow, JAX, Scikit-learn, large language models (LLMs), and machine learning concepts. Candidates interested in research-driven software development, predictive algorithms, data analytics, and production-ready AI systems should review the eligibility requirements carefully before applying.

If you are searching for Sony Research India internship opportunities, remote data science internships, AI/ML internships for students, or machine learning research opportunities in India, read the complete details below.

Sony Research India Internship 2026 – Job Overview

Important: The LinkedIn job title is “Data Science Intern,” while the description refers to the position as an “AI Intern.” The article uses Data Science Intern as the primary title and describes the responsibilities according to the supplied listing.

About Sony Research India

Sony Research India is part of Sony’s research and development ecosystem, which works across multiple locations around the world, including Japan, the United States, Europe, and Asia.

The organization focuses on creating new technologies, products, and services that support Sony Group’s diverse businesses, spanning electronics, entertainment, and financial services. Its research activities cover emerging technologies, including artificial intelligence, data analytics, and advanced computational systems.

Sony Research India aims to encourage research excellence by developing engineering and research talent. Its work brings together technical exploration, experimentation, and practical engineering to address complex problems and create innovative solutions.

For students interested in AI, machine learning, predictive algorithms, and large-scale data analysis, this internship offers an opportunity to explore how research ideas can be translated into practical software assets.

Sony Research India Data Science Intern Job Description

The selected intern will contribute to research and development activities involving predictive algorithms, video analysis architectures, and machine learning systems.

The role combines data exploration, model development, software engineering, experimentation, and performance evaluation. Candidates may work with complex datasets, identify behavioural patterns, develop useful features, and evaluate AI/ML techniques for specific objectives.

The internship also emphasizes the transition from experimentation to implementation. This means candidates should be prepared not only to explore machine learning models but also to write clean, modular, and production-oriented code.

The supplied job description highlights several important areas:

• Analysis of large and high-dimensional datasets.
• Data cleaning, feature engineering, and behavioural pattern discovery.
• Development and optimization of AI/ML algorithms.
• Research involving video analysis and large language models.
• Implementation of machine learning pipelines using Python.
• Collaboration with engineering teams and business stakeholders.
• Offline model verification and online A/B testing methodologies.
• Deployment and scaling of models and pipelines in modern cloud environments.

Candidates should understand that this is a technically demanding opportunity focused on research and engineering rather than a basic data-entry or general business analytics internship.

Key Responsibilities of a Sony Research India Intern

1. Analyze Large and Complex Datasets

One of the major responsibilities is working with large datasets containing numerous features, observations, and potentially noisy information.

The intern may help clean, transform, explore, and analyze data to identify meaningful patterns. This can involve identifying missing values, understanding distributions, detecting unusual observations, and selecting features that are useful for machine learning models.

Candidates should understand data preprocessing, exploratory data analysis, feature engineering, and statistical reasoning.

The ability to convert raw data into a structured format suitable for model development is an important part of applied data science.

2. Analyze Data Annotations and Extract Insights

Data annotations provide labels or descriptive information that help machine learning systems learn from examples. Depending on the task, annotations may describe objects, events, actions, or other relevant information in a dataset.

The intern will help analyze annotations and translate them into actionable insights.

This requires attention to detail, an understanding of data quality, and the ability to interpret structured information correctly. Candidates should be comfortable examining datasets, checking inconsistencies, and determining how annotation quality affects model performance.

3. Develop and Optimize AI/ML Algorithms

The internship involves designing, building, testing, and optimizing machine learning algorithms.

Candidates should have a strong understanding of supervised and unsupervised learning, model evaluation, loss functions, and bias mitigation.

Depending on the project, machine learning work may involve training models, comparing alternative approaches, tuning parameters, evaluating results, and identifying ways to improve performance.

A good understanding of the machine learning lifecycle—from data preparation and model training to evaluation and iteration—will be useful.

4. Work on Video Analysis and Predictive Algorithms

The job description specifically mentions video analysis algorithms and predictive architectures.

Video analysis can involve processing sequences of images or frames to identify patterns, objects, activities, or events. Unlike ordinary image classification, video analysis may require understanding temporal relationships between frames and changes over time.

Candidates interested in computer vision should understand the fundamentals of image processing, video data, feature extraction, and machine learning evaluation.

Experience with computer vision projects, video classification, object detection, action recognition, or related research can help demonstrate relevant technical ability. These are examples of useful project areas, not additional mandatory qualifications stated in the listing.

5. Explore Large Language Models (LLMs)

The listing identifies large language models as one of the required technical areas.

LLMs are machine learning models designed to process and generate language. Depending on the project, work involving LLMs can include experimentation, evaluation, analysis of model outputs, and integration with software systems.

Candidates should be familiar with the basic principles of modern AI models and be able to explain their own practical experience with machine learning or language-model applications.

A strong understanding of model evaluation and responsible experimentation is particularly useful when comparing approaches and analyzing results.

6. Collaborate with Engineering and Business Teams

The intern will work across engineering divisions and strategic business units.

This involves translating technical findings into understandable metrics, communicating experimental results, and connecting model performance to business objectives.

For example, a model may perform well on one evaluation metric but fail to meet the actual requirements of a project. Engineers must therefore interpret results in context and explain the trade-offs involved.

Clear communication, teamwork, documentation, and the ability to explain technical concepts are valuable skills for this responsibility.

7. Build Scalable and Production-Ready Code

The role involves writing clean, modular, and production-oriented software.

Candidates should understand how to organize Python code, use functions and modules, handle exceptions, and develop reusable components. Familiarity with testing, version control, and reproducible experiments can also be beneficial.

The objective is to move beyond isolated experiments and contribute to software that can be maintained, evaluated, and scaled within a modern engineering environment.

8. Participate in Model Evaluation and Experimentation

The intern may help develop rigorous offline verification frameworks and contribute to online A/B testing methodologies.

Offline evaluation involves testing a model against a prepared dataset or evaluation framework before relying on it in a live environment. A/B testing compares alternative approaches under defined conditions to understand their relative performance.

Candidates should be comfortable with evaluation metrics, experimental design, data leakage prevention, and the interpretation of results.

The ability to document experiments and draw evidence-based conclusions is important in research and applied machine learning.

Required Technical Skills

According to the supplied listing, candidates should demonstrate skills in AI/ML, particularly video analysis algorithms and LLMs, along with strong Python proficiency.

Python Programming

Python is central to data science and machine learning workflows. Candidates should be comfortable writing Python programs, manipulating data, organizing code, and debugging errors.

Useful areas to review include:

• Variables, functions, classes, and modules.
• Lists, dictionaries, sets, and other data structures.
• File handling and exception handling.
• Data processing and transformation.
• NumPy and data-oriented programming concepts.
• Writing readable, reusable, and modular code.

PyTorch

PyTorch is a machine learning framework widely used for deep learning research and model development.

Candidates should understand tensors, model definitions, training loops, loss functions, optimizers, and evaluation workflows if they claim practical PyTorch experience.

A personal project involving image classification, video processing, or another machine learning task can help demonstrate these skills.

TensorFlow

TensorFlow is another framework used to build and train machine learning and deep learning models.

Useful foundational topics include tensors, neural network layers, model training, evaluation, and data pipelines.

Candidates should focus on understanding how models are developed and evaluated rather than merely memorizing library functions.

JAX

JAX is a numerical computing library used for high-performance numerical operations and machine learning research.

Exposure to array operations, automatic differentiation, and accelerated computation can be helpful for candidates interested in advanced model development.

The supplied listing names JAX among the core technical packages, so candidates should review the level of proficiency they can demonstrate honestly.

Scikit-learn

Scikit-learn provides tools for traditional machine learning, including classification, regression, clustering, preprocessing, and model evaluation.

Candidates should understand train-test splits, feature preprocessing, cross-validation, model selection, and evaluation metrics.

Practical knowledge of these concepts provides a useful foundation for both experimentation and applied machine learning.

Understanding the Preferred Data Engineering Skills

The listing identifies SQL, PySpark, Polars, and Arrow as good-to-have skills for handling large datasets.

SQL: Useful for retrieving, filtering, joining, aggregating, and analyzing structured data.

PySpark: Used for distributed data processing and working with large datasets across computing resources.

Polars: A data-processing library designed for efficient tabular data operations.

Apache Arrow: A technology for efficient in-memory columnar data representation and data interchange.

These tools can help engineers prepare data for machine learning, improve processing efficiency, and work with data-intensive systems. They are listed as preferred skills rather than the primary mandatory skills in the supplied description.

Eligibility Criteria for Sony Research India Internship 2026

Candidates should review the education and technical requirements before submitting an application.

Educational Qualification

The supplied description identifies candidates currently pursuing an advanced undergraduate degree or a relevant MS/MTech qualification in areas such as:

• Computer Science.
• Data Science.
• Statistics.
• Mathematics.
• A related quantitative discipline.

The original listing contains slightly unclear wording around the undergraduate qualification. Applicants should confirm the precise degree and enrolment requirements on LinkedIn before applying.

Technical Eligibility

Candidates should demonstrate practical knowledge of AI/ML, video analysis algorithms, and LLMs, along with advanced proficiency in Python and the listed machine learning packages.

Academic research, personal projects, internships, and practical model-development experience may help demonstrate these capabilities.

Other Important Considerations

Applicants should be prepared to work remotely from within India and follow the specified working schedule. They should also be comfortable with experimentation, analytical problem-solving, collaboration, and technical documentation.

The supplied description does not specify a minimum CGPA, graduation year, or a fixed list of eligible passing batches. Candidates should not assume a particular batch is eligible without checking the application requirements.

Internship Duration, Work Mode, and Schedule

The supplied LinkedIn listing provides the following arrangements:

• Work mode: Remote within India.
• Internship duration: Six months.
• Expected start: First week of November 2026.
• Working days: Monday to Friday.
• Working hours: 9:00 AM to 6:00 PM IST.
• Payment: Paid internship.

The exact stipend amount is not stated in the supplied description. Applicants should check the official listing or confirm the amount with the recruiting team.

Candidates should also confirm the start date, working arrangements, and any other internship conditions during the application process, as hiring details may change.

How to Prepare for the Sony Research India Data Science Internship

Candidates can strengthen their applications by preparing examples that demonstrate their technical knowledge and practical experience.

Build Relevant Projects

Consider developing one or two projects that demonstrate skills relevant to the role, such as:

• A video classification or action-recognition project.
• A machine learning pipeline using Python and Scikit-learn.
• A deep learning model built using PyTorch or TensorFlow.
• A data analysis project involving feature engineering and model evaluation.
• An LLM-based application with a clear evaluation approach.

These are suggested preparation projects, not requirements explicitly listed by Sony Research India.

Prepare to Explain Your Work

For each project, be ready to explain the problem, dataset, preprocessing steps, model selection, evaluation metrics, limitations, and results.

Interviewers may be interested in how you handled data quality, selected features, compared models, and interpreted performance.

Review Machine Learning Fundamentals

Revise supervised learning, unsupervised learning, overfitting, underfitting, loss functions, model evaluation, data leakage, and bias mitigation.

For video analysis and LLM-related work, focus on understanding the fundamentals and being able to explain any practical experience you list on your resume.

Highlight Your Python Skills

Include relevant projects, repositories, research work, or internships that demonstrate Python proficiency and the use of machine learning libraries.

Ensure your resume accurately represents your contribution to each project.

Why Consider This Internship?

This internship may be a good fit for students seeking practical experience in research-driven AI and data science.

Potential benefits include:

• Exposure to AI/ML research and engineering.
• Experience working with complex datasets.
• Opportunities to explore predictive algorithms and video analysis.
• Practice developing and evaluating machine learning models.
• Exposure to production-oriented Python code and scalable pipelines.
• Experience communicating technical results across teams.
• A remote working arrangement within India, according to the listing.

The role is particularly relevant to candidates who enjoy experimentation, programming, analytical problem-solving, and the process of turning research ideas into working software.

How to Apply for Sony Research India Data Science Intern Recruitment 2026

Interested candidates can follow these steps:

1. Open the LinkedIn job listing using the link below.
2. Read the complete job description and verify the educational requirements.
3. Prepare an updated resume highlighting Python, AI/ML, video analysis, LLMs, and relevant project experience.
4. Include relevant research, internships, GitHub repositories, or project links where appropriate.
5. Use LinkedIn’s available application process and provide the requested information.
6. Review your application carefully before submitting it.
7. Monitor LinkedIn and your registered email for any communication from the recruiting team.

Apply through : Click here

Job ID: 4478080141

The supplied LinkedIn listing indicates that the role was posted recently and had received over 100 applicants at the time of the provided information. Application status and availability can change, so check the live listing before applying.

Frequently Asked Questions (FAQs)

1. What is the role offered by Sony Research India?

The LinkedIn job title is Data Science Intern. The description focuses on AI/ML research and engineering, including predictive algorithms, video analysis, LLMs, and large-scale data processing.

2. Is the Sony Research India internship remote?

Yes. The supplied listing specifies remote work within India.

3. What is the duration of the internship?

The internship is described as a paid, six-month opportunity.

4. When is the internship expected to begin?

The supplied description states that the internship is scheduled to begin in the first week of November 2026. Applicants should confirm the date in the live listing.

5. What are the working hours?

The listed schedule is 9:00 AM to 6:00 PM IST, Monday through Friday.

6. Is the internship paid?

Yes, the supplied listing describes it as a paid internship. However, the exact stipend amount has not been provided.

7. What qualification is required?

The description refers to relevant advanced undergraduate study or MS/MTech-level study in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative discipline. Applicants should verify the exact degree requirement on LinkedIn.

8. Which programming language is required?

Python is the main programming language highlighted in the description.

9. Which machine learning libraries are mentioned?

The listing identifies PyTorch, TensorFlow, JAX, and Scikit-learn.

10. Is prior experience with big data tools mandatory?

SQL, PySpark, Polars, and Arrow are mentioned as good-to-have skills. They are not presented as the main mandatory technical requirements in the supplied description.

11. Are freshers eligible to apply?

Eligibility depends on the candidate’s current educational status and demonstrated technical skills. The description focuses on students pursuing relevant undergraduate or postgraduate qualifications rather than specifying a general fresher batch range.

12. How can candidates apply?

Candidates can review the requirements and use the LinkedIn application process .

Final Words

The Sony Research India Data Science Intern opportunity is worth exploring for students interested in advanced AI, machine learning, video analysis, LLMs, and data-intensive software systems. With a stated six-month paid duration and remote work within India, it offers a potential opportunity to develop research and engineering skills in a professional environment.

Before applying, carefully review the educational requirements, confirm the current application status, and prepare a resume that clearly demonstrates your Python proficiency and practical machine learning experience.