IBM Internship 2026 | Hiring for IBM Research/Research Software – Intern |Apply Now!

IBM Recruitment for the post of Research Intern. Students from various disciplines can apply for the IBM off-campus drive 2026. Interested and eligible candidates can read more details below.

IBM Recruitment 2026:

IBM Recruitment  Job Description:

IBM Recruitment is hiring candidates for the post of Research Intern.

IBM Recruitment  Job Responsibilities:

• Contributing to ongoing research and development projects.
• Working with datasets to investigate technical problems and develop practical solutions.
• Implementing algorithms, models, or software components related to the assigned project.
• Exploring machine learning, deep learning, generative AI, large language models, or AI agents.
• Developing and evaluating AI-driven solutions for real-world or enterprise applications.
• Reading technical and research papers to understand existing methods and identify possible improvements.
• Running experiments, comparing results, and documenting findings.
• Using programming tools, libraries, and development environments relevant to the project.
• Working with mentors and other team members to solve technical challenges.
• Exploring quantum algorithms and implementing research methods for projects focused on quantum computing, where applicable

IBM Recruitment Eligibility Criteria:

• B.E. / B.Tech
• M.E. / M.Tech (including Dual Degree programs)
• Ph.D.
• Minimum 70% or 7.0 CGPA and above in the pursuing degree
• The internship will be conducted between May and August 2027, for a maximum duration of 3 months.

IBM Recruitment Required skills:

• Coding skills in Python (including Pandas, NumPy) & Qiskit
• Strong grasp of Data Structures, Algorithms, and Problem Solving
• Linear Algebra, Probability, and Statistics
• VS Code, Jupyter Notebooks, Git
• AI/ML Fundamentals
  – supervised & unsupervised learning
  – classification
  – regression
  – neural networks
  – clustering
• Learning fundamentals and Data Manipulation/Analysis for large datasets
• AI libraries/frameworks: TensorFlow, PyTorch
• Deep Learning, Foundation Models, Large Language Models, Deep Learning, Generative AI, Transformers, and NLP
• Familiar with Generative AI frameworks such as LangChain and crew.ai.
• Expertise in unstructured data processing
• Theoretical foundations in quantum computing.
• Algorithms like QAOA and sampling-based diagonalization algorithms that have scalable demonstrations on today’s quantum computers
• Ability to read research papers on quantum algorithms and applications and implement their methodology
• AI Accelerator software stack
• Exposure to AI Agents, tool use, function calling, reasoning models
• Familiarity with techniques such as LoRA/PEFT, knowledge distillation, reinforcement learning, or RLHF/RLAIF is desirable.
  
• Ability to read, understand, and critically analyze research papers.
• Experience implementing ideas from research papers is highly desirable.
• Ability to reproduce research results and design-controlled experiments

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