Location : Pune / Remote-Hybrid
Company : Sciverse Solutions Pvt. Ltd.
Experience Level : 4–5 years
Employment Type : Full-time
Department : AI & Advanced Technology
About Sciverse
Sciverse is a deep-tech MedTech company developing AI-powered diagnostic platforms and smart healthcare solutions. Our product suite includes point-of-care analyzers, AI-first microscopy systems, and intelligent software for image, text, and sensor data analysis. At the frontier of diagnostics and digital health, we engineer meaningful impact at scale.
Role Overview
We are seeking a highly motivated and skilled Deep Learning and Computer Vision Engineer to join our core AI team. You will design, train, and deploy models for microscopy image analysis, diagnostic automation, embedded vision systems, and contribute toward exploring vision-language models (VLMs) for structured report generation.
This is a hands-on engineering role where ownership, research depth, and deployment focus go hand-in-hand.
Key Responsibilities
1. Model Development & Training
- Design and implement deep learning models for object detection, segmentation, classification, and metric learning.
- Work with real-world biomedical and diagnostic datasets including microscopy, photometry, and point-of-care device outputs.
- Apply image preprocessing, denoising, and augmentation pipelines to improve model robustness.
2. Model Optimization & Deployment
Optimize models for embedded and edge inference (using TensorRT, ONNX, OpenVINO, etc.).Quantize and prune models for integration into diagnostic hardware platforms.Collaborate with firmware and software teams for seamless deployment on custom devices.3. Computer Vision Pipeline Engineering
Build scalable and reusable vision pipelines for tasks like cell counting, boundary detection, morphology estimation, and more.Integrate multi-class detection and segmentation modules in no-code platforms like SciVision.4. Vision-Language Exploration
Experiment with transformer-based models and VLMs (e.g., BLIP, Flamingo, LLaVA, SAM + LLM) for microscopy captioning, report generation, or structured interpretations.Contribute to prompt design, fine-tuning, or hybrid modeling efforts.5. Collaboration & Innovation
Work with cross-functional teams including biology, embedded systems, and UI / UX to convert scientific problems into engineering models.Stay up to date with state-of-the-art methods in vision, multimodal AI, and biomedical imaging.Must-Have Skills
Strong foundation in deep learning (CNNs, Transformers, Vision Backbones, etc.)Experience with image classification, instance / semantic segmentation, object detectionProficient in PyTorch and optionally TensorFlowExperience with training on real-world noisy datasetsUnderstanding of model deployment, optimization (ONNX, TensorRT, TFLite), and performance profilingHands-on with OpenCV, NumPy, Pandas, and Scikit-learnStrong debugging and visualization skills (e.g., TensorBoard, WandB)Bonus / Nice-to-Have Skills
Familiarity with medical imaging (DICOM, TIFF, proprietary formats)Exposure to multi-modal or vision-language models (e.g., CLIP, SAM, BLIP, LLaVA)Knowledge of embedded vision (Jetson, Coral, RK3399) deploymentPublications or contributions to open-source in vision or biomedical AIFamiliarity with MLOps tools like MLflow, Docker, FastAPIWho You Are
Self-starter with a strong sense of ownershipPassionate about solving real-world healthcare challenges with AIEnjoys rapid prototyping, experimentation, and learningComfortable working in an agile, research-to-product environmentWhy Join Sciverse
Work on mission-driven healthcare technology with tangible global impactSolve unique AI and vision challenges at the intersection of biology, diagnostics, and embedded systemsBe part of a fast-growing, founder-led, engineering-driven teamOpportunity to take ideas from R&D to production in record timeTo Apply
Email your CV, portfolio (if any), and a short note on why you’re excited about this role to : info@sciverse.co.in