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We are seeking a highly motivated and experienced Senior Computer Vision Engineer to join our dynamic Engineering and Research team. The work involves leveraging the latest advancements in deep learning to create robust and highly accurate systems for image classification object detection and semantic segmentation. This position offers the opportunity to contribute to impactful projects work with the latest technologies and shape the future of technological innovation and research-driven solutions.
Roles & Responsibilities :
Lead Deep Learning Model Development: Architect design develop and implement state-of-the-art deep learning models for image classification object detection and semantic segmentation tasks.
Algorithm Research and Selection: Stay abreast of the latest research and advancements in deep learning for computer vision. Evaluate benchmark and select appropriate algorithms and architectures (e.g. CNNs Transformers GANs etc.) based on project requirements and performance metrics.
Data Strategy and Preprocessing: Collaborate with data scientists and engineers to define data collection strategies perform extensive data augmentation labeling and preprocessing to ensure optimal model training and performance.
Model Training and Optimization: Design and execute robust training methodologies including hyperparameter tuning regularization techniques and distributed training strategies to achieve high accuracy and efficiency.
Performance Evaluation and Analysis: Conduct rigorous model evaluation performance profiling error analysis and interpretability studies to identify areas for improvement and ensure robust model behavior in diverse scenarios.
Deployment and Integration: Work closely with software engineers to integrate trained deep learning models into production systems considering performance scalability and resource constraints.
Research and Innovation: Actively contribute to the teams research agenda identifying new opportunities proposing innovative solutions and potentially publishing research findings.
Mentorship and Knowledge Sharing: Provide technical leadership and mentorship to junior engineers fostering a culture of continuous learning and knowledge sharing within the team.
Cross-Functional Collaboration: Collaborate effectively with other R&D teams product managers and stakeholders to understand requirements define project scope and deliver impactful solutions.
Documentation: Maintain comprehensive documentation of models algorithms experiments and results.
Qualifications :
Educational qualification:
ME/M. Tech/MS (Electronics Computer Science or related)
Experience :
6 to 8 years of professional experience.
Mandatory/requires Skills :
Excellent programming & rapid prototyping skills in Python.
Exposure to Object Oriented Programming and Design Data structures / Algorithms is a must.
Expertise on OpenCV DLib Numpy.
Excellent knowledge on any/all of the given concepts in Computer Vision - namely Image Classification Object Detection and Semantic Segmentation developed using state of the art deep learning algorithms.
Hands on experience in developing efficient and real-time convolution neural network models.
Awareness of Machine learning concepts hyperparameters tunning metrics and training methods and able to make benchmarks with other SOTA models.
Hands on working experience with anyone of the deep learning frameworks - TensorFlow Caffe Pytorch Keras MXNet Theano.
Experience on Foundation Models especially with EVA & DINO a big plus. Well conversed with MLOps concepts (Hands on experience with mlflow a big plus)
Exposure to model compression and pruning in deep learning.
Familiarity with GPU computing (CUDA OpenCL) HPC and and should have hands on experience in local GPU Linux servers or cloud machine learning service providers like AWS Azure etc.
Strong Problem Solving & Communication skills.
Highly Motivated Creative and a Team player.
Responsible on taking the ownership of modules/projects as well as contributing/collaborating the team with individual contributions.
Preferred Skills :
Experience/exposure to usage of Open-Source technologies State of Art models and understanding of famous model backbones.
Knowledge on containerizing the CV applications as docker or pod and REST API services for DL inference modules.
Experience of CV solution deployment on Edge (NVIDIA etc.) would be big plus.
Additional Information :
Why Bosch Research At Bosch Research you will experience a startup culture within a global corporate environment providing access to cutting-edge research significant computing infrastructure including large-scale LLM farms and real-world challenges that demand immediate solutions. Join us to architect scalable impactful and state-of-the-art Agentic AI solutions.
Remote Work :
No
Employment Type :
Full-time
Full-time