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Applied AI Engineer - Computer Vision

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Applied AI Engineer - Computer Vision

Endimension Technology Private Limited

Applied AI Engineer - Computer Vision

Skills

Deep LearningPythonPyTorchData AnalysisMachine LearningAI

22 days ago

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Important information


Contract type:

Permanent

Location:

Mumbai, Maharashtra, India

Work mode:

Onsite

Published on:

3 October 2026

What they need


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

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