AI / Machine Learning Engineer Remote
2 weeks ago
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, 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
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