AI / Machine Learning Engineer [ Remote]

Your Role

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.

What We’re Looking For

● 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.

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