Generative AI Engineer Intern

Generative AI Engineer Intern - Job Description

About DigiDxDoc

DigiDxDoc is revolutionizing pathology diagnostics through an end-to-end digital pathology platform that combines cutting-edge AI technology with clinical excellence. We are on a mission to democratize pathology diagnosis by making advanced digital diagnostics accessible and affordable globally.

Position Overview

Role:
Generative AI Engineer Intern (Paid)

Duration:
6 months with strong conversion opportunity to full-time

Location:
Koramangala, Bangalore

Compensation:
Competitive stipend with performance-based incentives

About the Opportunity

Join our AI team at a pivotal growth stage as we scale our digital pathology platform that's transforming cancer diagnosis and healthcare delivery. This is a rare opportunity to work on production-grade generative AI systems that directly impact patient outcomes, working alongside seasoned AI/ML leaders and clinical experts.

What You will Work On

Core Responsibilities

AI Model Development:
Design, implement, and optimize generative AI models for pathology image analysis, automated reporting and diagnostic assistance

Agentic AI Systems:
Build autonomous AI agents for workflow automation, quality control and intelligent case routing in our digital pathology platform

Computer Vision:
Develop and fine-tune deep learning models for whole slide image (WSI) analysis, tumour detection, and biomarker quantification

LLM Integration:
Implement large language models for automated pathology report generation, natural language processing of clinical data, and conversational AI interfaces

Research & Innovation:
Explore state-of-the-art generative AI techniques (GANs, diffusion models, transformer architectures) for novel pathology applications

Production Deployment:
Work with the engineering team to deploy AI models at scale on our cloud platform serving hospitals and labs across multiple countries

Who You Are

Required Qualifications

Currently pursuing or recently completed B.Tech/M.Tech/MS in Computer Science, AI/ML, or related field

Strong foundation in machine learning, deep learning, and computer vision

Hands-on experience with PyTorch or TensorFlow

Proficiency in Python and understanding of software engineering best practices

Familiarity with generative AI concepts (GANs, VAEs, diffusion models, or LLMs)

Understanding of transformer architectures and attention mechanisms

Preferred Qualifications

Experience with medical imaging or computational pathology

Published research or projects in generative AI, computer vision, or related domains

Familiarity with MLOps tools and practices (Docker, Kubernetes, MLflow, etc.)

Knowledge of cloud platforms (AWS, GCP, Azure)

Experience with libraries like Hugging Face Transformers, Stable Diffusion, or OpenAI APIs

Understanding of explainable AI and model interpretability techniques

Key Attributes We Value

Curiosity & Learning Agility:
Passion for staying current with rapidly evolving AI research and eagerness to experiment with new techniques

Problem-Solving Mindset:
Ability to break down complex problems and develop practical, scalable solutions

Ownership:
Takes initiative and drives projects from concept to deployment with minimal supervision

Collaboration:
Works effectively with cross-functional teams including engineers, pathologists, and product managers

Impact-Driven:
Motivated by the opportunity to improve healthcare outcomes through technology

Attention to Detail:
Understands that in healthcare AI, precision and reliability are paramount

What You will Gain

Learning & Growth

Clinical Exposure:
Work alongside pathologists and healthcare professionals to understand real-world clinical workflows

Cutting-Edge Tech Stack:
Hands-on experience with the latest in generative AI, cloud computing, and healthcare technology

Research Opportunities:
Potential to publish research papers and present at conferences

Domain Expertise:
Deep knowledge of digital pathology, medical imaging, and healthcare AI regulations

Career Development

Conversion Pathway:
High-performing interns receive full-time offers with competitive compensation and equity

Growth Trajectory:
Clear path from intern → AI Engineer → Senior AI Engineer/AI Lead

Ownership:
Lead significant features and modules as a core team member

Industry Recognition:
Work on products used by hospitals, research institutions, and healthcare systems globally

Work Environment

Startup Culture:
Fast-paced, innovative environment where your contributions directly shape product direction

Flexibility:
Hybrid work model with flexibility around core working hours

Resources:
Access to GPU compute, datasets, and tools needed for AI development

Team:
Work with a diverse team including clinicians and experienced engineers