AI / Machine Learning Engineer [ Remote]

As our AI/ML Engineer – Computer Vision, you will:

• Build, train, and deploy computer vision models for tasks such as image segmentation, anomaly detection, and 3D scan analysis in dental imaging.
• Collaborate with our full-stack team to integrate CV models into production, ensuring scalability and HIPAA-compliant security.
• Design pipelines for image preprocessing, annotation, augmentation, and evaluation.
• Explore and apply state-of-the-art methods (CNNs, vision transformers, UNet variants, MONAI, etc.) to dental image analysis.
• Optimize model performance for accuracy, inference speed, and cost-efficiency.
• Work closely with product leads and clients to translate clinical challenges into AI solutions.
• Stay ahead of the curve by testing new research and technologies in vision + generative AI.

Job Type

Part-time

Pay

Rs170,000.00 - Rs210,000.00 per month

Expected hours

40 per week

Application Question(s)

• Can you walk me through your experience with Python and one of the major deep learning frameworks (PyTorch or TensorFlow)? Which do you prefer and why?
• Have you implemented or trained models for image segmentation, anomaly detection, or object detection? If so, describe one project.
• Have you deployed a machine learning model into production (via Docker, APIs, or cloud)? What challenges did you face?
• Can you describe a time you designed a data preprocessing pipeline (annotation, augmentation, cleaning)? How did it improve results?
• Give an example of a project where the scope or priorities shifted. How did you adapt?
• What is your expected salary?
• If selected, when can you join?

Work Location

Remote

• 3–4 years of experience in computer vision, ML, or applied AI (academic + industry combined).
• Strong background in Python with experience in PyTorch or TensorFlow.
• Hands-on experience with OpenCV, MONAI, or similar CV libraries.
• Familiarity with image segmentation, anomaly detection, or medical/dental imaging a strong plus.
• Understanding of deep learning architectures (CNNs, transformers, UNets, etc.).
• Experience deploying ML models in production (Docker, APIs, cloud environments).
• Bonus: Knowledge of 3D imaging, medical AI, or HIPAA-compliant data pipelines.
• Strong problem-solving skills and ability to thrive in a startup environment where priorities shift quickly.