AI Research Intern – Deep Learning and TensorFlow

Job Summary

NeuralWorks is looking for a passionate AI Research Intern with a strong interest in Deep Learning, TensorFlow, and cutting-edge AI innovations. This internship is designed for individuals eager to gain practical experience in applied AI research while working alongside a team of highly skilled professionals. The role provides a unique opportunity to contribute to real-world projects, build advanced models, and deepen your understanding of AI frameworks in a dynamic and collaborative environment.


Key Responsibilities

  • Assist in the design, training, and evaluation of deep learning models using TensorFlow and related libraries.
  • Support research activities in areas such as computer vision, NLP, reinforcement learning, and generative AI.
  • Collaborate with senior researchers to develop, test, and optimize AI algorithms.
  • Perform data preprocessing, augmentation, and model fine-tuning to improve accuracy and efficiency.
  • Document research findings, experiment results, and technical insights.
  • Stay updated with the latest AI research papers, frameworks, and technologies.
  • Contribute to the development of internal tools, scripts, and workflows for AI experiments.

Required Skills and Qualifications

  • Currently pursuing a Bachelor’s/Master’s/PhD in Computer Science, Artificial Intelligence, Data Science, or related fields.
  • Strong foundation in machine learning, neural networks, and probability/statistics.
  • Hands-on experience with TensorFlow (preferred) or PyTorch.
  • Proficiency in Python and libraries such as NumPy, Pandas, and Matplotlib.
  • Understanding of key concepts such as CNNs, RNNs, LSTMs, GANs, and transformers.
  • Familiarity with research methodologies, data handling, and model evaluation metrics.
  • Strong problem-solving, critical thinking, and analytical skills.

Experience

  • Prior coursework, projects, or internships related to deep learning or AI research is highly desirable.
  • Exposure to GPU computing and cloud platforms (AWS, GCP, or Azure) is a plus.
  • Freshers with strong academic and project-based experience are encouraged to apply.

Working Hours

  • Flexible working hours with an expectation of 20–30 hours per week for part-time interns or full-time availability during summer/winter internships.
  • Remote and hybrid options are available depending on project requirements.

Knowledge, Skills, and Abilities

  • Ability to read, interpret, and implement research papers.
  • Strong communication skills for discussing technical concepts with both technical and non-technical teams.
  • Ability to work independently as well as collaboratively in a team setting.
  • High adaptability to new tools, frameworks, and emerging research directions.

Benefits

  • Opportunity to work on cutting-edge AI research projects with industry experts.
  • Gain hands-on exposure to TensorFlow and advanced AI frameworks.
  • Flexible work arrangements to balance academics and research.
  • Internship completion certificate with potential for a full-time role upon performance.
  • Access to mentorship, workshops, and internal training programs.
  • Networking opportunities with professionals and researchers in the AI field.

Why Join NeuralWorks

At NeuralWorks, we are committed to pioneering the future of AI by combining innovation, research, and real-world applications. As an intern, you will not only expand your technical expertise but also gain insights into the practical aspects of AI development. You will be part of a culture that values curiosity, creativity, and growth. This is more than an internship—it’s a stepping stone to becoming an impactful AI researcher.


How to Apply

Interested candidates should submit the following to our careers page or email:

  • Updated resume/CV highlighting academic background and projects.
  • A brief cover letter explaining your interest in AI research and TensorFlow.
  • Links to GitHub, Kaggle, or published papers (if available).

Shortlisted candidates will be contacted for an online technical assessment and interview.

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