Research Intern - AI

The interview process at GE Healthcare typically starts with a timed online test that evaluates coding proficiency and basic aptitude. The technical interview dives deep into AI fundamentals, research methodology, and hands‑on experience with frameworks like TensorFlow and PyTorch. HR focuses on cultural fit, communication skills and the candidate's motivation to work in healthcare AI. Preparation should include revisiting recent AI research papers and practicing coding problems under time pressure.

GE Healthcare promotes a collaborative, innovation‑driven culture where engineers and scientists are encouraged to experiment and fail fast. Employees benefit from structured mentorship programs, flexible work arrangements and a strong emphasis on work‑life balance, making it an attractive place for early‑career researchers.

Currently pursuing a PhD in Computer Science, Data Science, Artificial Intelligence or a closely related field from a recognized institute; strong foundation in deep learning, computer vision and generative AI; minimum CGPA/percentage of 7.5/75%; no active backlogs; ability to work full‑time for the internship duration; excellent communication skills in English.

Round 1: Online assessment covering coding (Python/C++) and quantitative aptitude → Round 2: Technical interview focusing on AI/ML concepts, research experience and problem‑solving → Round 3: HR interview assessing cultural fit, communication skills and internship logistics

GE Healthcare is a global leader in medical technology, digital solutions and diagnostics. With a presence in over 140 countries, the company combines deep clinical expertise with cutting‑edge engineering to create products that improve patient outcomes and streamline healthcare delivery. In India, GE Healthcare has built a strong ecosystem of research labs, innovation centers and collaborations with premier academic institutions, fostering a culture where scientific curiosity meets real‑world impact. The Research Intern – AI role is positioned within GE Healthcare’s AI Innovation Lab in Bengaluru. As an intern, you will work side‑by‑side with senior scientists, data engineers and product managers to design, prototype and evaluate next‑generation AI algorithms that enhance medical imaging workflows. The internship offers a rare opportunity to contribute to projects that directly influence how radiologists diagnose diseases, how surgeons plan procedures, and how hospitals manage data at scale. **Key Responsibilities** 1. Develop and fine‑tune deep‑learning models for image analytics, super‑resolution reconstruction, and inverse imaging problems. 2. Implement generative AI pipelines (diffusion models, GANs, foundation vision models) for medical image synthesis, data augmentation and report generation. 3. Explore and integrate vision‑language models and retrieval‑augmented generation techniques to build multimodal AI systems for clinical decision support. 4. Conduct experiments on large‑scale datasets, evaluate model performance against clinical benchmarks, and document findings. 5. Collaborate with cross‑functional teams to translate research prototypes into production‑ready code using TensorFlow, PyTorch and Keras. 6. Stay updated with state‑of‑the‑art publications, benchmark against competing solutions, and propose novel research directions. 7. Write clean, modular Python/C++ code and contribute to shared code repositories and model registries. 8. Present results in internal seminars, prepare technical reports, and assist in drafting patents or research papers. **Tech Stack**: Python, C++, TensorFlow, PyTorch, Keras, HuggingFace Transformers, Vector Databases, CUDA, Docker, Git, AWS/GCP for large‑scale training. **Growth Path**: Successful interns may receive a full‑time offer as a Research Engineer or Data Scientist, with clear pathways to senior research roles, project leadership, or PhD‑level collaborations across GE’s global AI network. **Why Join GE Healthcare?** The internship places you at the intersection of AI research and life‑saving healthcare applications. You gain exposure to high‑impact problems, mentorship from world‑class experts, and access to massive medical imaging datasets that are rarely available elsewhere. Moreover, GE’s commitment to diversity, inclusion and continuous learning ensures a supportive environment where innovative ideas are encouraged and rewarded.