Principal AI/ML Engineer

Experience: 5.00 years Salary: Confidential (based on experience) Expected Notice Period: 30 Days Shift: (GMT 05:30) Asia/Kolkata (IST) Opportunity Type: Office () Placement Type: Full Time Permanent position(Payroll and Compliance to be managed by: An early-stage healthcare startup) (*Note: This is a requirement for one of Uplers' client - An early-stage healthcare startup) What do you need for this opportunity Must have skills required Python, C , PyTorch, Computer Vision, Cnn, Detection, CUDA, TensorRT, NVIDIA, Holoscan, Medical Imaging, DICOM, Radiology, Healthcare, PACS, MONAI, ISO 13485, Deepstream, HL7, MRI, Machine learning workflows, AI/ML, Deep Learning, Vision Transformers, anomaly detection, Segmentation, CDSCO , SaMD , Jetson , Triton Inference Server , Medical Open Network for AI, Ultrasound , real-time clinical decision , diagnostic hardware An early-stage healthcare startup is Looking for: Industry: HealthTech | Artificial Intelligence (AI) | Medical Devices | Diagnostic Imaging | Software as a Medical Device (SaMD) Location: Greater Noida / Remote (India) 5 Days work from home Department: AI/ML Engineering Diagnostics Principal AI/ML Engineer About KM The Principal AI/ML Engineer at KM is a founding AI leadership role, responsible for building and owning the company's end-to-end AI stack for medical imaging. This is not a traditional ML research positionit combines AI architecture, edge deployment, MLOps, regulatory engineering, and technical leadership. The role focuses on developing AI-powered clinical decision support systems that assist doctors during diagnosis. Rather than replacing clinicians, the AI provides real-time anomaly detection, segmentation, and recommendations while the doctor makes the final clinical decision, aligning with the company's Human-in-the-Loop approach. KM is building a highly scalable, tech-enabled diagnostic network designed to democratize access to automated medical diagnostics. We are retrofitting legacy diagnostic hardware with state-of-the-art Edge AI to provide real-time clinical decision support. Our mission is to bridge the gap in Tier-2 and Tier-3 healthcare by deploying affordable, multi-modality AI assistants (Ultrasound, Endoscopy, CT, MRI, and X-ray) that empower local doctors and sonographers. The Role We are seeking a Principal AI/ML Engineer to lead the architecture, training, and edge deployment of our proprietary diagnostic AI models. You will not be building an autonomous AI doctor you will be building a high-performance Class B Software as a Medical Device (SaMD) designed to act as a human-in-the-loop clinical assistant. You will leverage the full NVIDIA healthcare stack to process both live sensor streams (USG, Endoscopy) and volumetric data (CT, MRI). Key Responsibilities Multimodal AI Development: Design, train, and optimize Deep Learning architectures (CNNs, Vision Transformers) for anomaly detection, bounding-box generation, and real-time segmentation across live 60fps video and 3D volumetric datasets. Edge Streaming Pipelines: Architect ultra-low latency inference pipelines for live Ultrasound and Endoscopy using the NVIDIA Holoscan framework and zero-copy GPU memory management. Model Optimization: Convert and compress trained PyTorch/MONAI models using NVIDIA TensorRT and deploy them locally via Triton Inference Server on Jetson or DGX edge hardware. Clinical Data Orchestration: Build secure, DPDPA-compliant pipelines to ingest, anonymize, and process DICOM and PACS data from our clinical partners for model training. Regulatory Engineering: Work directly with our compliance team to ensure all model training, validation, and version control strictly adhere to ISO 13485 standards required for CDSCO Class B SaMD clearance. Requirements 5 years of AI/ML experience with strong Computer Vision expertise. Advanced proficiency in Python, with hands-on C/C and CUDA. Strong experience with PyTorch, MONAI, CNNs, and Vision Transformers. Hands-on experience with the NVIDIA AI stack (Holoscan, TensorRT, Triton, DeepStream, Jetson/DGX). Experience building and deploying Edge AI solutions for real-time inference. Knowledge of medical imaging standards (DICOM, HL7, PACS) and radiology workflows. Experience optimizing AI models for production deployment. Understanding of ISO 13485, Class B SaMD, and regulated AI development is highly preferred. Strong system architecture, technical leadership, Experience: 5.00 years Salary: Confidential (based on experience) Expected Notice Period: 30 Days Shift: (GMT 05:30) Asia/Kolkata (IST) Opportunity Type: Office () Placement Type: Full Time Permanent position(Payroll and Compliance to be managed by: An early-stage healthcare startup) (*Note: This is a requirement for one of Uplers' client - An early-stage healthcare startup) What do you need for this opportunity Must have skills required Python, C , PyTorch, Computer Vision, Cnn