Machine Learning Engineer

4 years

0 Lacs

Posted:23 hours ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

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:

own the core AI systems powering OpEase

  1. Reconstructing 3D anatomical structures from orthogonal 2D X-rays

    , and
  2. Building intelligent auto-selection and auto-suggestion logic

    for measurement and planning tools inside our surgical workflow.

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

What You Will Build (Very Specific):

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

• Landmark/keypoint detection models for vertebrae, femur/tibia, pelvis, etc.

• Heatmap regression networks for anatomical feature extraction

auto-selection system

• End-to-end inference pipeline integrated into our MERN + Cornerstone-based viewer

• Continuous evaluation pipelines for accuracy, latency, and failure-case analysis


Responsibilities:

• Architect and train models for 2D→3D anatomical prediction using multi-view geometry, implicit fields, NeRF/DVGO variants, or transformer-based approaches

• Build landmark detection modules for calibration, templating, and surgical planning

• Design the autosuggestion engine: tool intent prediction, context modelling, clinical-rule integration

• Manage data pipelines for X-ray preprocessing, augmentation, versioning, annotation QC, and synthetic dataset generation

• Validate models with surgeons; refine based on clinical feedback

• Deploy models to production (REST endpoints, ONNX/TensorRT optimization, GPU/CPU fallback)

• Maintain experiment logs, metrics dashboards, and detailed model documentation


Requirements (High Priority & Non-Negotiable):

Minimum 4 years of full-time experience

computer vision for geometry problems

PyTorch

DICOM/X-ray/medical imaging

• Proven ability to independently take a model from idea → dataset → training → evaluation → production

• Strong mathematical grounding in 3D geometry, camera models, coordinate transforms, and projection systems

• Excellent documentation and communication skills


Bonus (Big Plus):

• Experience with NeRFs, implicit neural representations, depth inference, or differentiable rendering

• Experience building autosuggestion systems, ranking models, or intent prediction in complex workflows


Why Join:

• You will own the foundational AI layer for India’s most advanced orthopedic planning platform

• Clear, well-scoped problems and direct access to clinicians who use your models

• Chance to build category-defining medical AI from the ground up

• High ownership, high-impact role in a company scaling rapidly across India and global markets


Hybrid role with periodic clinical onsite work.

Compensation: ₹18–24 LPA + ESOPs.

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