Clinical Onboarding Specialist (Hybrid) 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 using advanced geometry tools and clinical logic. Role Overview: We're hiring a Clinical Onboarding Specialist to ensure surgeons have a smooth, high-quality onboarding experience. You will conduct product demos, train clinicians, manage early adoption, and act as the primary point of contact during the first phase of their OpEase journey. This is a hybrid role with periodic hospital visits. Responsibilities: Lead end-to-end onboarding for surgeons and clinical teams Deliver structured training on all core workflows (X-ray upload, calibration, measurement tools, patient data workflows) Provide timely support, troubleshoot issues, and coordinate with engineering for escalations Maintain detailed tracking of onboarding progress and adoption metrics Collect user feedback and suggest process improvements Ensure every new surgeon becomes an active, confident user within defined timelines Requirements (High Priority): Minimum 2 years of professional experience in customer success, healthcare operations, SaaS onboarding, or clinical support Excellent communication and presentation skills, especially with senior clinicians Strong problem-solving ability and comfort managing multiple onboardings simultaneously High attention to detail and clear documentation skills Fast learner with the ability to understand technical and clinical workflows Comfortable with hybrid work, local travel, and on-site hospital trainings Strong ownership mindset and ability to work independently Why Join: Work directly with surgeons, product teams, and leadership Develop deep expertise in medtech, clinical workflows, and SaaS adoption Fast-growth role as OpEase scales across India and international markets Hybrid role with significant on-site travel. Compensation: ?46 LPA .
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) • Landmark/keypoint detection models for vertebrae, femur/tibia, pelvis, etc. • Heatmap regression networks for anatomical feature extraction • A model-driven auto-selection system that identifies which OpEase tool the surgeon requires based on image context and user behaviour • 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 in ML/Deep Learning with shipped models in production • Strong experience in computer vision for geometry problems : keypoints, reconstruction, pose estimation, volumetric prediction • Hands-on expertise with PyTorch , multi-GPU training, and advanced optimization techniques • Prior work with DICOM/X-ray/medical imaging OR demonstrably adjacent experience (e.g., industrial CV, robotics perception, pose estimation) • 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.
Clinical Onboarding Specialist (Hybrid) 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 using advanced geometry tools and clinical logic. Role Overview: We’re hiring a Clinical Onboarding Specialist to ensure surgeons have a smooth, high-quality onboarding experience. You will conduct product demos, train clinicians, manage early adoption, and act as the primary point of contact during the first phase of their OpEase journey. This is a hybrid role with periodic hospital visits. Responsibilities: • Lead end-to-end onboarding for surgeons and clinical teams • Deliver structured training on all core workflows (X-ray upload, calibration, measurement tools, patient data workflows) • Provide timely support, troubleshoot issues, and coordinate with engineering for escalations • Maintain detailed tracking of onboarding progress and adoption metrics • Collect user feedback and suggest process improvements • Ensure every new surgeon becomes an active, confident user within defined timelines Requirements (High Priority): • Minimum 2 years of professional experience in customer success, healthcare operations, SaaS onboarding, or clinical support • Excellent communication and presentation skills, especially with senior clinicians • Strong problem-solving ability and comfort managing multiple onboardings simultaneously • High attention to detail and clear documentation skills • Fast learner with the ability to understand technical and clinical workflows • Comfortable with hybrid work, local travel, and on-site hospital trainings • Strong ownership mindset and ability to work independently Why Join: • Work directly with surgeons, product teams, and leadership • Develop deep expertise in medtech, clinical workflows, and SaaS adoption • Fast-growth role as OpEase scales across India and international markets Hybrid role with significant on-site travel. Compensation: ₹4–6 LPA .