3 Inference Pipelines Jobs

As a Computer Vision Engineer at RNT Health Insights, you will be at the forefront of researching, developing, and implementing spatiotemporal algorithms for detecting and delineating lesions in real-time during endoscopic video feeds. Your role will involve collaborating with a multidisciplinary team of AI researchers, gastroenterologists, and software engineers to enhance both spatial and temporal accuracy in lesion detection. You will be responsible for designing preprocessing pipelines, optimizing models, and ensuring low latency, high-performance deployment in clinical settings. Key Responsibilities - Algorithm Development: Research, develop, and implement spatiotemporal techniques combined with CNN and other spatial models for real-time lesion detection in endoscopic video streams. - Temporal Analysis: Investigate and apply state-of-the-art techniques (e.g., LSTMs, 3D CNNs) to model temporal dependencies in video-based data for improved lesion tracking and detection. - Model Integration: Integrate temporal models with existing CNN-based spatial models to create efficient, end-to-end pipelines for real-time inference during endoscopy procedures. - Preprocessing & Inference Pipelines: Design and implement robust video preprocessing (e.g., frame extraction, image enhancement, noise reduction) and inference pipelines that ensure smooth integration with endoscopic hardware and software systems. - Post-processing Optimization: Work on post-processing techniques to improve lesion localization, classification, and segmentation accuracy, and ensure consistent performance in different clinical settings. - Model Optimization: Fine-tune models for deployment on constrained hardware platforms, ensuring low-latency performance without compromising accuracy. - Collaborative Research: Collaborate with research teams to explore and incorporate cutting edge temporal models, multi-frame fusion techniques, and domain-specific innovations in medical video analysis. - Performance Benchmarking: Benchmark models against datasets, assess performance (accuracy, speed, robustness), and optimize for real-time clinical use. Qualifications And Expectations - Bachelor's/ Master's/ PhD in Computer Science, Electrical Engineering, or closely related fields with a focus on Artificial Intelligence, Machine Learning, or Computer Vision. - Strong foundation in computer vision principles, including image processing techniques, feature extraction methodologies, and neural network architectures. - Proficiency with deep learning frameworks such as TensorFlow, Keras, or PyTorch. - Proficiency in programming languages, particularly Python and C++, with the ability to write clean, efficient, and well-documented code. - Solid grasp of machine learning algorithms and methodologies, including experience with real-time inference and model optimization for deployment in resource-constrained environments. - Ability to engage with and interpret relevant scientific literature, staying updated on the latest advancements in computer vision and machine learning as they apply to medical applications. - Ability to communicate ideas clearly and effectively, both in oral and written formats. - Self-motivated individual who works well in a team, and is open to giving and receiving honest feedback. If you are passionate about computer vision and eager to contribute to cutting-edge healthcare technology, we would love to hear from you!,

As a Machine Learning Engineer at Aera Technology, you will play a crucial role in designing, implementing, monitoring, and maintaining the machine learning systems that power our Aera Decision Cloud platform. Your responsibilities will involve working on new and challenging engineering problems to operationalize data science, collaborating closely with experts in Data Science, Engineering, and DevOps teams, and designing state-of-the-art Machine Learning approaches. Your main tasks will include building core machine learning infrastructure, such as distributed systems, development tools, model serving, and inference pipelines. Additionally, you will take end-to-end ownership of developing Machine Learning systems from data pipelines to training, hosting, and inference pipelines. It is essential to have strong programming skills in languages like C++, Go, Java, and Python, along with experience in working with large data sets and pipelines using frameworks like Dask and Ray. Ideally, you should possess a B.E./B.Tech M.E/M.Tech/M.S in Computer Science or Computer Engineering, along with 3-8 years of experience in software engineering and architecture. Having at least 2 years of experience in designing and deploying Machine Learning Systems and familiarity with libraries like Scikit-learn, Pandas, PyTorch, Tensorflow, and Keras will be beneficial for this role. Experience in building containerized applications using Docker and Kubernetes, Agile Methodology, GITOps, and Jira is also desired. In our dynamic environment, hosted on AWS/Azure/GCP with Kubernetes infrastructure, you will have the opportunity to contribute to the transformation of decision-making processes for enterprises worldwide. If you are passionate about creating a sustainable, intelligent, and efficient world, Aera Technology is the right place for you. Join our diverse teams across different global locations and be a part of our journey to revolutionize decision intelligence. At Aera Technology, we value our team members and offer a range of benefits to support them and their families at various life stages. In addition to a competitive salary and company stock options, we provide comprehensive medical insurance, term insurance, accidental insurance, paid time off, maternity leave, and more. We prioritize professional and personal development by offering unlimited access to online courses and people manager development programs. Our flexible working environment promotes a healthy work-life balance, and our office facilities include a fully-stocked kitchen with snacks and beverages to keep you refreshed throughout the day.,

About the Role: We are looking for a highly skilled AI & Deep Learning Engineer to develop intelligent solutions that support and optimize our manual and semi-automated product assembly lines . The role involves defect detection using vision systems, process improvement through AI, and potential robotic integration. The ideal candidate will work closely with our teams in both India and China . Key Responsibilities: Design and implement AI models for product defect detection, assembly verification, and process enhancement. Develop and train computer vision models (e.g., object detection, segmentation, anomaly detection) on real assembly data. Work on model deployment for real-time edge inference using Jetson, Raspberry Pi, or similar. Travel between India and China to collect data, collaborate with factory teams, and test AI models on-site. Integrate AI solutions with production systems, sensors, and possibly PLCs/IoT infrastructure. Optimize model performance for reliability, speed, and low power use in production environments. Required Skills: Strong hands-on experience in ML/DL frameworks like PyTorch, TensorFlow, OpenCV. Experience in vision-based defect detection, segmentation, and object tracking. Familiarity with deployment tools like ONNX, TensorRT, TFLite. Prior experience working in or with manufacturing, QA, or assembly environments. Willingness and ability to travel between India and China. Preferred: Experience with robotic arms or vision-guided systems. Familiarity with manufacturing protocols (Modbus, OPC-UA, MQTT).