Artificial Intelligence Engineer Intern

SETV HEALTHCARE TECHNOLOGY PRIVATE LIMITED

Position:

Location:

Employment Type:

Duration:

Working Hours:

Shift Options:

• 7:00 PM – 1:00 AM (IST)

Company Description:

SETV.W

Duties and Responsibilities

• Research, design, and implement machine learning and deep learning models for image, video, text, and multi-modal healthcare data.
• Work on real-world healthcare datasets including medical imaging (CT, MRI, ultrasound), tabular clinical data, and electronic health records.
• Preprocess, clean, and annotate data using tools like NumPy, OpenCV, and Pandas.
• Train, fine-tune, and evaluate models using TensorFlow, PyTorch, Hugging Face Transformers, or ONNX.
• To work with LLMs and agents 
• Collaborate with web, DevOps, and UI/UX teams for seamless AI model integration.
• Build and document modular AI pipelines using tools like MLflow, FastAPI, or Flask.
• Contribute to performance benchmarking, error analysis, and model explain ability (e.g., Grad-CAM, SHAP, LIME).
• Conduct literature reviews and propose innovative enhancements to existing models.
• Support deployment of models in production and edge environments (via TorchScript, TFLite, ONNX, etc.).
• Maintain version-controlled notebooks and adhere to reproducible ML practices.

Requirements

• Strong understanding of ML/DL algorithms (CNNs, RNNs, Transformers, etc.).
• Experience with at least one deep learning framework (PyTorch, TensorFlow, or Keras).
• Solid Python programming skills and hands-on knowledge of data science libraries (NumPy, Pandas, Scikit-learn).
• Familiarity with real-world datasets and domain challenges in computer vision or NLP.
• Good grasp of evaluation metrics (Accuracy, F1-score, AUC, IoU, Dice, etc.).
• Exposure to model deployment, containerization (Docker), or API integration is a plus.
• Strong problem-solving skills and ability to work independently on research problems.

Preferred Skills (Bonus):

• Experience with healthcare-specific AI tasks (segmentation, detection, classification, triage).
• Familiarity with DICOM/NIfTI data formats and libraries like MONAI or SimpleITK.
• Knowledge of Hugging Face, LangChain, or OpenAI API.
• Understanding of edge deployment strategies (NVIDIA Jetson, Coral, etc.).
• Research exposure (published papers, blog posts, or GitHub contributions).

Qualifications:

• Education:

  Currently pursuing or recently completed a Bachelor's or Master’s degree or PHD in Computer Science, Data Science, AI, Biomedical Engineering, or a related field.

• Portfolio:

  Strong GitHub profile, Kaggle experience, or AI project portfolio required.

• Domain Knowledge:

  Awareness of medical AI standards (HIPAA, FDA guidelines) is an advantage.

Selection Process (3 Rounds):

1. Resume Screening

   – Based on portfolio, skills, and relevance.

2. Technical Interview

   – Problem-solving, ML concepts, and project discussion.

3. Founding Office Interview(Optional)

   – Strategic thinking, innovation mindset, and cultural alignment.

What We Offer:

• Real-World Impact:

  Work on AI models that improve healthcare outcomes.

• Mentorship:

  Get guidance from leading experts in AI and medical tech.

• Career Growth:

  Opportunity for conversion to a paid part-time role and optional full time opportunities.

• Flexible Remote Work:

  Structured hours that support learning and productivity.

• Recognition:

  Performance-based incentives and loyalty rewards.