Imaging IQ

Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers who love solving problems. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. People who are looking to extend artificial intelligence into unexplored areas. Your primary focus will be in applying deep learning and artificial intelligence techniques to the domain of medical image analysis. Responsibilities Selecting features, building and optimizing classifier engines using deep learning techniques. Understanding the problem and applying the suitable image processing techniques Use techniques from artificial intelligence/deep learning to solve supervised and unsupervised learning problems. Understanding and designing solutions for complex problems related to medical image analysis by using Deep Learning/Object Detection/Image Segmentation. Recommend and implement best practices around the application of statistical modeling. Create, train, test, and deploy various neural networks to solve complex problems. Develop and implement solutions to fit business problems which may include applying algorithms from a standard statistical tool, deep learning or custom algorithm development. Understanding the requirements and designing solutions and architecture in accordance with them. Participate in code reviews, sprint planning, and Agile ceremonies to drive high-quality deliverables. Design and implement scalable data science architectures for training, inference, and deployment pipelines. Ensure code quality, readability, and maintainability by enforcing software engineering best practices within the data science team. Optimize models for production, including quantization, pruning, and latency reduction for real-time inference. Drive the adoption of versioing strategies for models, datasets, and experiments (e.g., using MLFlow, DVC). Contribute to the architectural design of data platforms to support large-scale experimentation and production workloads. Skills and Qualifications Strong software engineering skills in Python (or other languages used in data science) with emphasis on clean code, modularity, and testability. Excellent understanding and hands-on of Deep Learning techniques such as ANN, CNN, RNN, LSTM, Transformers, VAEs etc. Must have experience with Tensorflow or PyTorch framework in building, training, testing, and deploying neural networks. Experience in solving problems in the domain of Computer Vision. Knowledge of data, data augmentation, data curation, and synthetic data generation. Ability to understand the complete problem and design the solutions that best fit all the constraints. Knowledge of the common data science and deep learning libraries and toolkits such as Keras, Pandas, Scikit-learn, Numpy, Scipy, OpenCV etc. Good applied statistical skills, such as distributions, statistical testing, regression, etc. Exposure to Agile/Scrum methodologies and collaborative development practices. Experience with the development of RESTful APIs. The knowledge of libraries like FastAPI and the ability to apply it to deep learning architectures is essential. Excellent analytical and problem-solving skills with a good attitude and keen to adapt to evolving technologies. Experience with medical image analysis will be an advantage. Experience designing and building ML architecture components (e.g., feature stores, model registries, inference servers). Solid understanding of software design patterns, microservices, and cloud-native architectures. Expertise in model optimization techniques (e.g., ONNX conversion, TensorRT, model distillation) Education: BE/B Tech MS/M Tech (will be a bonus) Experience: 3-5 Years

Senior Data Scientist (Deep Learning and Artificial Intelligence) Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers who love solving problems. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. People who are looking to extend artificial intelligence into unexplored areas. Your primary focus will be in applying deep learning and artificial intelligence techniques to the domain of medical image analysis. Responsibilities Selecting features, building and optimizing classifier engines using deep learning techniques. Understanding the problem and applying the suitable image processing techniques Use techniques from artificial intelligence/deep learning to solve supervised and unsupervised learning problems. Understanding and designing solutions for complex problems related to medical image analysis by using Deep Learning/Object Detection/Image Segmentation. Recommend and implement best practices around the application of statistical modeling. Create, train, test, and deploy various neural networks to solve complex problems. Develop and implement solutions to fit business problems which may include applying algorithms from a standard statistical tool, deep learning or custom algorithm development. Understanding the requirements and designing solutions and architecture in accordance with them is important. Participate in code reviews, sprint planning, and Agile ceremonies to drive high-quality deliverables. Design and implement scalable data science architectures for training, inference, and deployment pipelines. Ensure code quality, readability, and maintainability by enforcing software engineering best practices within the data science team. Optimize models for production, including quantization, pruning, and latency reduction for real-time inference. Drive the adoption of versioing strategies for models, datasets, and experiments (e.g., using MLFlow, DVC). Contribute to the architectural design of data platforms to support large-scale experimentation and production workloads. Skills and Qualifications Strong software engineering skills in Python (or other languages used in data science) with emphasis on clean code, modularity, and testability. Excellent understanding and hands-on of Deep Learning techniques such as ANN, CNN, RNN, LSTM, Transformers, VAEs etc. Must have experience with Tensorflow or PyTorch framework in building, training, testing, and deploying neural networks. Experience in solving problems in the domain of Computer Vision. Knowledge of data, data augmentation, data curation, and synthetic data generation. Ability to understand the complete problem and design the solutions that best fit all the constraints. Knowledge of the common data science and deep learning libraries and toolkits such as Keras, Pandas, Scikit-learn, Numpy, Scipy, OpenCV etc. Good applied statistical skills, such as distributions, statistical testing, regression, etc. Exposure to Agile/Scrum methodologies and collaborative development practices. Experience with the development of RESTful APIs. The knowledge of libraries like FastAPI and the ability to apply it to deep learning architectures is essential. Excellent analytical and problem-solving skills with a good attitude and keen to adapt to evolving technologies. Experience with medical image analysis will be an advantage. Experience designing and building ML architecture components (e.g., feature stores, model registries, inference servers). Solid understanding of software design patterns, microservices, and cloud-native architectures. Expertise in model optimization techniques (e.g., ONNX conversion, TensorRT, model distillation) Education : BE/B Tech MS/M Tech (will be a bonus) Experience : 3+ Years Job Type: Full-time Ability to commute/relocate: Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Do you have experience leading teams in AI Development? Do you have experience creating software architecture for production environment in AI applications? Experience: Deep learning: 3 years (Required) Computer vision: 3 years (Required) PyTorch: 3 years (Required) Work Location: In person

Senior Data Scientist (Deep Learning and Artificial Intelligence) Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers who love solving problems. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. People who are looking to extend artificial intelligence into unexplored areas. Your primary focus will be in applying deep learning and artificial intelligence techniques to the domain of medical image analysis. Responsibilities Selecting features, building and optimizing classifier engines using deep learning techniques. Understanding the problem and applying the suitable image processing techniques Use techniques from artificial intelligence/deep learning to solve supervised and unsupervised learning problems. Understanding and designing solutions for complex problems related to medical image analysis by using Deep Learning/Object Detection/Image Segmentation. Recommend and implement best practices around the application of statistical modeling. Create, train, test, and deploy various neural networks to solve complex problems. Develop and implement solutions to fit business problems which may include applying algorithms from a standard statistical tool, deep learning or custom algorithm development. Understanding the requirements and designing solutions and architecture in accordance with them is important. Participate in code reviews, sprint planning, and Agile ceremonies to drive high-quality deliverables. Design and implement scalable data science architectures for training, inference, and deployment pipelines. Ensure code quality, readability, and maintainability by enforcing software engineering best practices within the data science team. Optimize models for production, including quantization, pruning, and latency reduction for real-time inference. Drive the adoption of versioing strategies for models, datasets, and experiments (e.g., using MLFlow, DVC). Contribute to the architectural design of data platforms to support large-scale experimentation and production workloads. Skills and Qualifications Strong software engineering skills in Python (or other languages used in data science) with emphasis on clean code, modularity, and testability. Excellent understanding and hands-on of Deep Learning techniques such as ANN, CNN, RNN, LSTM, Transformers, VAEs etc. Must have experience with Tensorflow or PyTorch framework in building, training, testing, and deploying neural networks. Experience in solving problems in the domain of Computer Vision. Knowledge of data, data augmentation, data curation, and synthetic data generation. Ability to understand the complete problem and design the solutions that best fit all the constraints. Knowledge of the common data science and deep learning libraries and toolkits such as Keras, Pandas, Scikit-learn, Numpy, Scipy, OpenCV etc. Good applied statistical skills, such as distributions, statistical testing, regression, etc. Exposure to Agile/Scrum methodologies and collaborative development practices. Experience with the development of RESTful APIs. The knowledge of libraries like FastAPI and the ability to apply it to deep learning architectures is essential. Excellent analytical and problem-solving skills with a good attitude and keen to adapt to evolving technologies. Experience with medical image analysis will be an advantage. Experience designing and building ML architecture components (e.g., feature stores, model registries, inference servers). Solid understanding of software design patterns, microservices, and cloud-native architectures. Expertise in model optimization techniques (e.g., ONNX conversion, TensorRT, model distillation) Education : BE/B Tech MS/M Tech (will be a bonus) Experience : 3+ Years Job Type: Full-time Ability to commute/relocate: Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Do you have experience leading teams in AI Development? Do you have experience creating software architecture for production environment in AI applications? Experience: Deep learning: 3 years (Required) Computer vision: 3 years (Required) PyTorch: 3 years (Required) Work Location: In person

Full Stack Developer – Node.js & React.Js Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. We are looking for a highly motivated and technically proficient Full Stack Developer with expertise in Node.js and React.Js or Angular to join our development team. This role is ideal for individuals who thrive in dynamic environments, take ownership of their work, and aim to build cutting-edge, cloud-ready applications with a focus on performance, scalability, and maintainability. Responsibilities Lead and contribute to the design and development of modern, scalable full stack applications using Node.js, React.Js or Angular, and REST APIs. Architect, develop, and maintain efficient and reusable code components with modular design approaches. Develop robust backend logic using Node.js, Express.js, and integrate with MySQL, MongoDB, and other data sources. Build dynamic and responsive front-end user interfaces using React.Js or Angular, HTML5, CSS3, Bootstrap, and JavaScript/TypeScript. Design and implement RESTful APIs for seamless front-end/backend communication. Write non-blocking, asynchronous, secure code following best practices including error handling, logging, and performance optimization. Implement component-based design principles, reusability patterns, and scalable UI modules. Integrate third-party SDKs, APIs, and external services into the application ecosystem. Create test scripts using tools such as Jasmine, Karma, or equivalent JavaScript testing libraries. Automate builds, test, and deployment processes using CI/CD pipelines (e.g., Jenkins, Artifactory). Participate in code reviews, sprint planning, and Agile ceremonies to drive high-quality deliverables. Maintain proper documentation for code, configurations, and architectural decisions. Skills and Qualifications Strong hands-on experience in Node.js, Express.js, and REST API development. Front-end development experience using React.Js or Angular, HTML5, CSS3, JavaScript, and TypeScript. Experience integrating MySQL and MongoDB databases with backend services. Knowledge of WebSocket communication and real-time data exchange via Socket.io. Familiarity with cloud-ready architectures and modern deployment practices. Proficient in using Git, Bitbucket, and related version control systems. Experience in responsive design, mobile-first development, and cross-browser compatibility. Working knowledge of unit testing using Jasmine, Karma, or similar frameworks. Experience with task runners such as Grunt or Gulp. Solid understanding of user authentication and authorization across systems and environments. Ability to implement best practices for performance tuning, caching, security, and scalability. Exposure to Agile/Scrum methodologies and collaborative development practices. Good to Have Experience with AWS Lambda, AWS API Gateway, or other cloud-native services. Familiarity with chat framework development, real-time messaging, or bot integration. Knowledge of Cassandra, Redis, or other NoSQL/Key-Value stores. Understanding of containerization tools like Docker, and orchestration platforms such as Kubernetes. Background in microservices architecture, DevOps practices, and service mesh concepts. Soft Skills Strong problem-solving and analytical thinking. Excellent written and verbal communication. Proactive, self-driven, and enthusiastic about learning and experimenting with new technologies. Team-oriented with a growth mindset and ability to work independently. Experience Required : 3-5 Years Education : B.E/B.Tech/MCA Job Type: Full-time Pay: ₹1,000,000.00 - ₹1,200,000.00 per year Supplemental Pay: Performance bonus Ability to commute/relocate: Gurgaon, Haryana: Reliably commute or planning to relocate before starting work (Preferred) Experience: React: 3 years (Required) APIs: 3 years (Required) REST: 3 years (Required) RDBMS: 3 years (Required) Work Location: In person

Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. We are looking for a highly motivated and technically proficient Full Stack Developer with expertise in Node.js and React.Js or Angular to join our development team. This role is ideal for individuals who thrive in dynamic environments, take ownership of their work, and aim to build cutting-edge, cloud-ready applications with a focus on performance, scalability, and maintainability. Responsibilities Lead and contribute to the design and development of modern, scalable full stack applications using Node.js, React.Js or Angular, and REST APIs. Architect, develop, and maintain efficient and reusable code components with modular design approaches. Develop robust backend logic using Node.js, Express.js, and integrate with MySQL, MongoDB, and other data sources. Build dynamic and responsive front-end user interfaces using React.Js or Angular, HTML5, CSS3, Bootstrap, and JavaScript/TypeScript. Design and implement RESTful APIs for seamless front-end/backend communication. Write non-blocking, asynchronous, secure code following best practices including error handling, logging, and performance optimization. Implement component-based design principles, reusability patterns, and scalable UI modules. Integrate third-party SDKs, APIs, and external services into the application ecosystem. Create test scripts using tools such as Jasmine, Karma, or equivalent JavaScript testing libraries. Automate builds, test, and deployment processes using CI/CD pipelines (e.g., Jenkins, Artifactory). Participate in code reviews, sprint planning, and Agile ceremonies to drive high-quality deliverables. Maintain proper documentation for code, configurations, and architectural decisions. Skills and Qualifications Strong hands-on experience in Node.js, Express.js, and REST API development. Front-end development experience using React.Js or Angular, HTML5, CSS3, JavaScript, and TypeScript. Experience integrating MySQL and MongoDB databases with backend services. Knowledge of WebSocket communication and real-time data exchange via Socket.io. Familiarity with cloud-ready architectures and modern deployment practices. Proficient in using Git, Bitbucket, and related version control systems. Experience in responsive design, mobile-first development, and cross-browser compatibility. Working knowledge of unit testing using Jasmine, Karma, or similar frameworks. Experience with task runners such as Grunt or Gulp. Solid understanding of user authentication and authorization across systems and environments. Ability to implement best practices for performance tuning, caching, security, and scalability. Exposure to Agile/Scrum methodologies and collaborative development practices. Good to Have Experience with AWS Lambda, AWS API Gateway, or other cloud-native services. Familiarity with chat framework development, real-time messaging, or bot integration. Knowledge of Cassandra, Redis, or other NoSQL/Key-Value stores. Understanding of containerization tools like Docker, and orchestration platforms such as Kubernetes. Background in microservices architecture, DevOps practices, and service mesh concepts. Strong problem-solving and analytical thinking. Excellent written and verbal communication. Proactive, self-driven, and enthusiastic about learning and experimenting with new technologies. Team-oriented with a growth mindset and ability to work independently. Experience Required : 3-5 Years Education: B.E/B.Tech/MCA

System Administrator Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers who love solving problems. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. We are looking for a System Administrator to manage and optimize our on-premise and cloud infrastructure, ensuring reliability, security, and scalability for high-throughput AI workloads. As a System Administrator, you will be responsible for managing servers, storage, network, and compute infrastructure powering our AI development and deployment pipelines. You will ensure seamless handling of large medical imaging datasets (DICOM/NIfTI), maintain high availability for research and production systems Key Responsibilities Infrastructure & Systems Management Manage Linux-based servers, GPU clusters, and network storage for AI training and inference workloads. Configure and maintain message queue systems (RabbitMQ, ActiveMQ, Kafka) for large-scale, asynchronous AI pipeline execution. Set up and maintain service beacons and health checks to proactively monitor the state of critical services (XNAT pipelines, FastAPI endpoints, AI model inference servers). Maintain PACS integration, DICOM routing, and high-throughput data transfer for medical imaging workflows. Manage hybrid infrastructure (on-prem + cloud) including auto-scaling compute for large training tasks. Service Monitoring & Reliability Implement automated service checking for all production and development services using Prometheus, Grafana, or similar tools. Configure beacon agents to trigger alerts and self-healing scripts for service restarts when anomalies are detected. Set up log aggregation and anomaly detection to catch failures in AI processing pipelines early. Ensure 99.9% uptime for mission-critical systems and clinical services. Security & Compliance Enforce secure access control (IAM, VPN, RBAC, MFA) and maintain audit trails for all system activities. Ensure compliance with HIPAA, GDPR, ISO 27001 for medical data storage and transfer. Encrypt medical imaging data (DICOM/NIfTI) at rest and in transit. Automation & DevOps Develop automation scripts for service restarts, scaling GPU resources, and pipeline deployments. Work with DevOps teams to integrate infrastructure monitoring with CI/CD pipelines. Optimize AI pipeline orchestration with MQ-based task handling for scalable performance. Backup, Disaster Recovery & High Availability Manage data backup policies for medical datasets, AI model artifacts, and PostgreSQL/MongoDB databases. Implement failover systems for MQ brokers and imaging data services to ensure uninterrupted AI processing. Collaboration & Support Work closely with AI engineers and data scientists to optimize compute resource utilization. Support teams in troubleshooting infrastructure and service issues. Maintain license servers and specialized imaging software environments. Skills and Qualifications Required: 3+ years of Linux systems administration experience with a focus on service monitoring and high-availability environments. Experience with message queues (RabbitMQ, ActiveMQ, Kafka) for distributed AI workloads. Familiarity with beacons, service health monitoring, self-healing automation. Experience managing GPU clusters (NVIDIA CUDA, drivers, dockerized AI workflows). Hands-on with cloud platforms (AWS, GCP, Azure). Networking fundamentals (firewalls, VPNs, load balancers). Hands-on experience with GPU-enabled servers (NVIDIA CUDA, drivers, dockerized AI workflows). Experience managing large datasets (100GB–TB scale), preferably in healthcare or scientific research. Familiarity with cloud platforms (AWS EC2, S3, EKS or equivalents). Knowledge of cybersecurity best practices and compliance frameworks (HIPAA, ISO 27001). Preferred: Experience with PACS, XNAT, or medical imaging servers. Familiarity with Prometheus, Grafana, ELK stack, SaltStack beacons, or similar monitoring tools. Knowledge of Kubernetes or Docker Swarm for container orchestration. Basic scripting knowledge (Bash, Python) for task automation. Exposure to database administration (PostgreSQL, MongoDB). Scripting skills (Bash, Python, PowerShell) for automation and troubleshooting. Understanding of databases (PostgreSQL, MongoDB) used in AI pipelines. Education: BE/B Tech, MS/M Tech (will be a bonus) Experience: 3-5 Years Job Type: Full-time Work Location: In person

System Administrator Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers who love solving problems. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. We are looking for a System Administrator to manage and optimize our on-premise and cloud infrastructure, ensuring reliability, security, and scalability for high-throughput AI workloads. As a System Administrator, you will be responsible for managing servers, storage, network, and compute infrastructure powering our AI development and deployment pipelines. You will ensure seamless handling of large medical imaging datasets (DICOM/NIfTI), maintain high availability for research and production systems Key Responsibilities Infrastructure & Systems Management Manage Linux-based servers, GPU clusters, and network storage for AI training and inference workloads. Configure and maintain message queue systems (RabbitMQ, ActiveMQ, Kafka) for large-scale, asynchronous AI pipeline execution. Set up and maintain service beacons and health checks to proactively monitor the state of critical services (XNAT pipelines, FastAPI endpoints, AI model inference servers). Maintain PACS integration, DICOM routing, and high-throughput data transfer for medical imaging workflows. Manage hybrid infrastructure (on-prem + cloud) including auto-scaling compute for large training tasks. Service Monitoring & Reliability Implement automated service checking for all production and development services using Prometheus, Grafana, or similar tools. Configure beacon agents to trigger alerts and self-healing scripts for service restarts when anomalies are detected. Set up log aggregation and anomaly detection to catch failures in AI processing pipelines early. Ensure 99.9% uptime for mission-critical systems and clinical services. Security & Compliance Enforce secure access control (IAM, VPN, RBAC, MFA) and maintain audit trails for all system activities. Ensure compliance with HIPAA, GDPR, ISO 27001 for medical data storage and transfer. Encrypt medical imaging data (DICOM/NIfTI) at rest and in transit. Automation & DevOps Develop automation scripts for service restarts, scaling GPU resources, and pipeline deployments. Work with DevOps teams to integrate infrastructure monitoring with CI/CD pipelines. Optimize AI pipeline orchestration with MQ-based task handling for scalable performance. Backup, Disaster Recovery & High Availability Manage data backup policies for medical datasets, AI model artifacts, and PostgreSQL/MongoDB databases. Implement failover systems for MQ brokers and imaging data services to ensure uninterrupted AI processing. Collaboration & Support Work closely with AI engineers and data scientists to optimize compute resource utilization. Support teams in troubleshooting infrastructure and service issues. Maintain license servers and specialized imaging software environments. Skills and Qualifications Required: 3+ years of Linux systems administration experience with a focus on service monitoring and high-availability environments. Experience with message queues (RabbitMQ, ActiveMQ, Kafka) for distributed AI workloads. Familiarity with beacons, service health monitoring, self-healing automation. Experience managing GPU clusters (NVIDIA CUDA, drivers, dockerized AI workflows). Hands-on with cloud platforms (AWS, GCP, Azure). Networking fundamentals (firewalls, VPNs, load balancers). Hands-on experience with GPU-enabled servers (NVIDIA CUDA, drivers, dockerized AI workflows). Experience managing large datasets (100GB–TB scale), preferably in healthcare or scientific research. Familiarity with cloud platforms (AWS EC2, S3, EKS or equivalents). Knowledge of cybersecurity best practices and compliance frameworks (HIPAA, ISO 27001). Preferred: Experience with PACS, XNAT, or medical imaging servers. Familiarity with Prometheus, Grafana, ELK stack, SaltStack beacons, or similar monitoring tools. Knowledge of Kubernetes or Docker Swarm for container orchestration. Basic scripting knowledge (Bash, Python) for task automation. Exposure to database administration (PostgreSQL, MongoDB). Scripting skills (Bash, Python, PowerShell) for automation and troubleshooting. Understanding of databases (PostgreSQL, MongoDB) used in AI pipelines. Education: BE/B Tech, MS/M Tech (will be a bonus) Experience: 3-5 Years Job Type: Full-time Work Location: In person