Careers

Foundational AI Research Intern – Healthcare

Research & Engineering — Remote / Hybrid

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Explicity – Healthcare AI Innovation Lab

At Explicity, we are on a mission to build the future of intelligent healthcare systems powered by cutting-edge artificial intelligence. We are seeking a highly motivated and research-driven AI Research Intern to join our core team in developing next-generation Healthcare AI models from the ground up.

This is a high-impact, hands-on role designed for individuals who want to work beyond theory and actively contribute to building real-world AI systems. As an AI Research Intern at Explicity, you will collaborate closely with our research and engineering team to design, develop, train, and optimize machine learning and deep learning models using real-world healthcare datasets.

This is not a routine internship. You will be directly involved in foundational model architecture design, experimentation, evaluation, and performance optimization. You will help shape the technical backbone of our Healthcare AI products and contribute to solutions that have meaningful real-world impact on patient care and medical decision-making.

Key Responsibilities

  • Design and implement machine learning and deep learning models from scratch
  • Work with structured and unstructured healthcare datasets
  • Perform data preprocessing, feature engineering, and pipeline development
  • Train models in GPU environments and optimize for performance and scalability
  • Conduct research experiments and analyze results
  • Improve model accuracy, robustness, and efficiency
  • Document research methodologies and technical decisions
  • Collaborate with product and engineering teams to translate research into deployable systems

Ideal Candidate

  • Strong foundation in Machine Learning and Deep Learning
  • Proficient in Python with hands-on experience in PyTorch or TensorFlow
  • Experience training and fine-tuning models in GPU environments
  • Understanding of neural networks, optimization techniques, and model evaluation metrics
  • Research-oriented mindset with strong analytical and problem-solving skills
  • Passion for building impactful AI solutions in the healthcare domain

Why Join Explicity?

  • Opportunity to build foundational Healthcare AI systems from scratch
  • Work in a serious, innovation-driven startup environment
  • Contribute to technology that can transform patient care
  • Direct exposure to advanced AI research and real-world deployment challenges
  • Be part of a mission-driven team building the future of Healthcare AI

Educational Background

Any one of the following:

  • B.Tech / B.E. in Computer Science (AI/ML specialization preferred)
  • M.Tech / M.S. in Artificial Intelligence / Machine Learning / Data Science
  • PhD (ongoing or completed) in AI / ML / Computer Science or related field
  • Candidates without the above degrees but with exceptional practical experience and recognized AI/ML certifications may also apply.

Technical Skills (Must Have)

  • Strong Python programming skills
  • Hands-on experience with PyTorch or TensorFlow
  • Solid understanding of Machine Learning fundamentals (Regression, Classification, Optimization, Evaluation Metrics)
  • Experience building and training Deep Learning models (CNNs, RNNs, Transformers, etc.)
  • Experience working with real-world datasets
  • Familiarity with GPU-based training environments

Preferred Qualifications

  • Experience training models from scratch
  • Research publications or academic projects in AI/ML
  • Experience with healthcare or medical datasets
  • Knowledge of model deployment pipelines
  • Experience in experiment tracking and reproducible research workflows

Accepted Certifications

If no formal AI degree:

  • Machine Learning Specialization (Coursera / DeepLearning.AI)
  • Google Professional Machine Learning Engineer
  • AWS Machine Learning Specialty
  • Microsoft Azure AI Engineer
  • Strong Kaggle ranking or significant open-source AI contributions

What We Value

  • Strong analytical and research mindset
  • Ability to work independently in an early-stage startup environment
  • Curiosity, experimentation, and problem-solving attitude
  • High ownership and accountability