Machine Learning Engineer

Machine Learning Engineer (2D→3D Reconstruction & Workflow Intelligence)

OpEase Technologies builds a high-precision, web-based surgical planning platform for orthopedic and spine surgeons. Doctors use OpEase to securely store patient data, upload X-rays, calibrate, measure, and plan surgeries through advanced geometry tools and clinical logic.

Role Overview :

We’re hiring an ML Engineer who will

own the core AI systems powering OpEase

— specifically :

Reconstructing 3D anatomical structures from orthogonal 2D X-rays , and

Building intelligent auto-selection and auto-suggestion logic

for measurement and planning tools inside our surgical workflow.

This is not a research-only role. You will be responsible for

designing, training, validating, and deploying production-grade ML systems

that directly impact surgical decision-making. Clear problem statements and datasets will be provided; you are expected to execute with speed and rigor.

What You Will Build (Very Specific) :

• A robust

2D→3D spine / long-bone reconstruction model

using dual-view X-rays (AP + lateral)

auto-selection system

that identifies which OpEase tool the surgeon requires based on image context and user behaviour

Responsibilities :

Requirements (High Priority & Non-Negotiable) :

Minimum 4 years of full-time experience

in ML / Deep Learning with shipped models in production

computer vision for geometry problems : keypoints, reconstruction, pose estimation, volumetric prediction

PyTorch , multi-GPU training, and advanced optimization techniques

DICOM / X-ray / medical imaging

OR demonstrably adjacent experience (e.g., industrial CV, robotics perception, pose estimation)

Bonus (Big Plus) :

Why Join :

Hybrid role with periodic clinical onsite work.

Compensation : ₹18–24 LPA + ESOPs.