Applied AI Engineer - Computer Vision

Company Description
Endimension Technology is a healthcare Artificial Intelligence startup incubated at the Indian Institute of Technology (IIT) Bombay. We build AI-powered solutions for medical imaging and radiology, with the goal of improving diagnostic accuracy, efficiency and access to healthcare. Founded by computer science graduates from IIT Bombay, IIT Madras, and the University of Illinois at Urbana-Champaign, the team brings over a decade of industry experience to its mission.
Our team works closely with radiologists, hospitals and healthcare partners to develop and deploy AI solutions in real-world clinical environments.
Role Description
We are looking for an Applied AI Engineer – Computer Vision for a full-time, on-site role based in Navi Mumbai.
This role sits at the intersection of Computer Vision, AI model evaluation, data analysis and real-world healthcare applications.
You will work with medical imaging data such as X-ray, CT and MRI, evaluate AI model behavior, investigate errors and patterns, and translate those insights into improvements across models, data and AI workflows.
The role requires strong analytical thinking and the ability to go beyond simply running models — understanding why a model succeeds or fails and what can be done to improve it.
What You'll Do
Work with large medical imaging datasets including X-ray, CT and MRI
Run and evaluate AI models on real-world imaging data
Perform detailed false-positive, false-negative and error analysis
Visually analyze medical images and identify patterns behind model behavior
Collaborate closely with radiologists and domain experts to understand difficult cases and imaging findings
Identify opportunities to improve datasets, labels and model performance
Curate and organize data for training, validation and evaluation
Fine-tune, retrain, modify or combine models where appropriate
Develop post-processing and decision logic to improve overall system performance
Build Python tools and scripts for data analysis, visualization and model evaluation
Evaluate performance across different datasets, imaging conditions and real-world environments
Explore relevant research and experiment with ideas that can improve AI performance
Work with engineering and product teams to translate AI models into reliable healthcare products
Document experiments, findings and recommendations clearly
What We're Looking For
1–3 years of experience in Computer Vision, Applied AI, Machine Learning or a related field
Strong foundation in Computer Vision and Deep Learning
Strong programming skills in Python
Experience with PyTorch or similar deep-learning frameworks
Experience working with image datasets and evaluating AI/ML models
Understanding of classification, object detection and/or segmentation
Good understanding of model evaluation metrics such as precision, recall, sensitivity, specificity and false positives / false negatives
Strong analytical and problem-solving skills
Ability to investigate why a model is failing rather than treating it as a black box
Ability to visually analyze data and connect patterns in images with model predictions
Comfortable working with real-world, imperfect datasets
Good communication skills and ability to collaborate with domain experts
Curiosity and willingness to learn new technical and domain concepts
Bachelor's or Master's degree in Computer Science, Electronics, AI/ML or a related field
Good to Have
Exposure to medical imaging, radiology or healthcare AI
Experience working with X-ray, CT, MRI or other imaging datasets
Experience with dataset curation, annotation or label-quality analysis
Experience with model explainability or visualization techniques
Experience building evaluation or data-analysis pipelines
Participation in AI competitions, research projects, publications or open-source work
Interest in reading and experimenting with recent AI research
Experience in a startup or product-focused AI environment
Prior medical-imaging experience is helpful but not mandatory. Strong Computer Vision candidates who are interested in learning the healthcare domain are encouraged to apply.
Who Would Be a Good Fit?
You may be a strong fit if you enjoy questions such as:
Why is the model making this prediction?
What patterns are common across failure cases?
Is the issue caused by the data, labels, preprocessing or the model itself?
How can feedback from domain experts be translated into better AI systems?
We are looking for someone who enjoys deep technical investigation, experimentation and iterative improvement.
Benefits
Competitive salary and benefits
Opportunity to work on real-world AI problems in healthcare
Work with large-scale medical imaging datasets
Direct collaboration with radiologists and healthcare experts
Exposure to the complete applied-AI lifecycle — data, evaluation, modeling and deployment
High ownership and meaningful technical responsibility
Fast learning in a growing healthcare-AI startup
Opportunity to build technology that can directly impact patient care

Work arrangement
No