6 Torchvision Jobs

At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world. In the OCI AI Science org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. As a Data Scientist IV, you will lead the development of large-scale datasets and leverage machine learning and generative AI to advance Generative AI models. You will drive the design of benchmarking frameworks, define best practices for data quality and fairness, and partner with scientists, engineers, and product leaders to shape the org's data strategy. Key Responsibilities: Lead the design, development, and scaling of large, high-quality datasets to advance generative AI models in multimodal domains (e.g., text, vision, speech). Define data standards and best practices for acquisition, cleaning, augmentation, annotation, and evaluation to ensure fairness, diversity, and representativeness. Guide the integration of cutting-edge techniques (e.g., fine-tuning, RLHF, domain adaptation) into data generation and model alignment pipelines. Provide technical leadership in building scalable, reliable data pipelines and synthetic data platforms for production environments. Evaluate and operationalize research innovations, shaping how data preparation and generative AI methods transition into production-ready solutions. Partner with research, engineering, and product leaders to define long-term data strategy and accelerate the adoption of generative AI solutions at scale. Mentor and provide thought leadership to scientists and engineers, fostering a culture of data excellence and innovation Qualifications and Skills: Bachelors or Master's in Computer Science, Data Science, AI/ML, or related field with 6+ years of industry experience. Proficiency in Python and solid foundation in applied ML methods. Proficiency with Pytorch, Torchvision, OpenCV, and similar, as well as building and deploying DNN models in production. Experience building large-scale data pipelines for acquisition, cleaning, augmentation, and validation. Ability to evaluate datasets for distribution, diversity, anomalies and fairness to assess overall quality and suitability for generative AI. Experience with Computer Vision, NLP, Transformers, Large Language Models, Generative AI, optimizations around LLM training and serving. Experience with Multimodal models a bonus. Familiarity with advanced techniques (e.g., RLHF, domain adaptation, data augmentation) and their application in generative AI workflows. Proven track record of delivering scalable, data-centric ML solutions. Excellent communication and leadership skills, with experience mentoring junior scientists/engineers and presenting technical strategies to senior stakeholders. Career Level - IC4

At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world. In the OCI AI Science org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. As a Data Scientist IV, you will lead the development of large-scale datasets and leverage machine learning and generative AI to advance Generative AI models. You will drive the design of benchmarking frameworks, define best practices for data quality and fairness, and partner with scientists, engineers, and product leaders to shape the org's data strategy. Key Responsibilities: Lead the design, development, and scaling of large, high-quality datasets to advance generative AI models in multimodal domains (e.g., text, vision, speech). Define data standards and best practices for acquisition, cleaning, augmentation, annotation, and evaluation to ensure fairness, diversity, and representativeness. Guide the integration of cutting-edge techniques (e.g., fine-tuning, RLHF, domain adaptation) into data generation and model alignment pipelines. Provide technical leadership in building scalable, reliable data pipelines and synthetic data platforms for production environments. Evaluate and operationalize research innovations, shaping how data preparation and generative AI methods transition into production-ready solutions. Partner with research, engineering, and product leaders to define long-term data strategy and accelerate the adoption of generative AI solutions at scale. Mentor and provide thought leadership to scientists and engineers, fostering a culture of data excellence and innovation Qualifications and Skills: Bachelors or Master's in Computer Science, Data Science, AI/ML, or related field with 6+ years of industry experience. Proficiency in Python and solid foundation in applied ML methods. Proficiency with Pytorch, Torchvision, OpenCV, and similar, as well as building and deploying DNN models in production. Experience building large-scale data pipelines for acquisition, cleaning, augmentation, and validation. Ability to evaluate datasets for distribution, diversity, anomalies and fairness to assess overall quality and suitability for generative AI. Experience with Computer Vision, NLP, Transformers, Large Language Models, Generative AI, optimizations around LLM training and serving. Experience with Multimodal models a bonus. Familiarity with advanced techniques (e.g., RLHF, domain adaptation, data augmentation) and their application in generative AI workflows. Proven track record of delivering scalable, data-centric ML solutions. Excellent communication and leadership skills, with experience mentoring junior scientists/engineers and presenting technical strategies to senior stakeholders. Career Level - IC4

You will be responsible for developing, fine-tuning, and evaluating vision-language models such as CLIP, Flamingo, BLIP, GPT-4V, LLaVA, among others. Your role will involve designing and constructing multimodal pipelines that fuse image/video inputs with natural language comprehension or generation. Working with extensive image-text datasets like LAION, COCO, Visual Genome for training and validation will be a key part of your job. You will also be implementing zero-shot/few-shot multimodal inference, retrieval, captioning, VQA (Visual Question Answering), grounding, etc. It is essential to collaborate closely with product teams, ML engineers, and data scientists to deliver practical multimodal applications. Additionally, optimizing model inference performance and resource utilization in production environments using ONNX, TensorRT, etc., will be expected. Conducting error analysis, ablation studies, and suggesting enhancements in visual-language alignment, as well as contributing to research papers, documentation, or patents if in a research-oriented team, are also part of the responsibilities. To excel in this role, you should hold a Bachelors/Masters/PhD in Computer Science, AI, Machine Learning, or a related field. You must possess at least 2+ years of experience in computer vision or NLP, with a minimum of 1+ year specifically in multimodal ML or VLMs. Strong proficiency in Python programming, along with hands-on experience in libraries like PyTorch, HuggingFace Transformers, OpenCV, torchvision, is required. Familiarity with VLM architectures such as CLIP, BLIP, Flamingo, LLaVA, Kosmos, GPT-4V, etc., is expected. You should also have prior experience in dataset curation, image-caption pair processing, and image-text embedding strategies. A solid grasp of transformers, cross-attention mechanisms, and contrastive learning will be advantageous for this role. This is a full-time position with a day shift schedule. The work location is in-person.,

We are looking for a Generative AI Engineer to join our team specializing in AI applications involving Large Language Models (LLMs), Vision-Language Models (VLMs, and Computer Vision (CV). As a Generative AI Engineer, your primary responsibilities will include fine-tuning and optimizing LLMs for various tasks like summarization, classification, Q&A, and creative generation. You will also have the opportunity to work with Vision-Language Models such as BLIP, MiniGPT, and Kosmos for tasks like image captioning, visual question answering, and retrieval. Additionally, you will contribute to training and evaluating Computer Vision models for tasks like image generation, detection, or editing. Moreover, you will be expected to implement and test various prompt engineering and LoRA-based fine-tuning approaches for different tasks. Your role will involve preprocessing and managing multi-modal datasets containing images and text, and creating training/evaluation pipelines. It is essential to write clean, modular, and well-documented code for training, inference, and deployment purposes. Collaboration with backend, product, and design teams to integrate models into real-world applications will also be a key aspect of your job. Keeping yourself updated with the latest papers and open-source projects in the Generative AI space is crucial for this role. To be considered for this position, you should hold a Bachelor's degree in Computer Science, Artificial Intelligence, or a related field. A minimum of 3 years of experience in machine learning or deep learning, particularly in NLP or computer vision domains, is required. Proficiency in Python, PyTorch, and libraries such as Transformers (Hugging Face), OpenCV, or TorchVision is essential. Hands-on experience with LLMs like GPT, BERT, LLaMA, or CV models such as CLIP and Stable Diffusion is preferred. Familiarity with transformers, attention mechanisms, tokenization, and embedding techniques is also expected. Being comfortable with datasets, training loops, and evaluation metrics will be beneficial for this role.,

Visionify is dedicated to leveraging the potential of Computer Vision and AI for various real-world applications. We are currently seeking a highly skilled, motivated, and enthusiastic Senior Computer Vision Engineer to play a crucial role in implementing our strategic plans. As a Senior Computer Vision Engineer at Visionify, you will be tasked with tackling cutting-edge challenges in the realm of Computer Vision by devising innovative algorithms and optimizations. The majority of our projects revolve around practical applications of Computer Vision, necessitating a strong grasp of contemporary model types such as Classification, Object detection, Object Recognition, OCR, LayoutML, and GAN networks. Proficiency in Pytorch is essential for this role, as it serves as our primary programming language. Familiarity with Azure and Azure ML Studio would be advantageous. Candidates applying for this position should remain abreast of the latest advancements and actively contribute to enhancing the Pytorch project's performance and accuracy. Your expertise in PyTorch and its underlying mechanisms will be pivotal in resolving customer challenges and offering valuable insights into product improvements. Experience in optimizing and streamlining models for deployment on edge devices, as well as converting models to NVIDIA TensorRT, will be highly valued. A strong foundation in Python programming is indispensable, given its widespread use in our organization for developing training and inference pipelines. Effective communication and presentation skills are also crucial. The ideal candidate will exhibit a deep passion for artificial intelligence and a commitment to staying updated on industry trends. **Responsibilities:** - Understanding business objectives and devising Computer Vision solutions that align with these goals, including developing training and inference frameworks and leveraging various ML technologies. - Building and optimizing Pytorch models for different runtime environments, including NVIDIA Jetson TensorRT. - Guiding the development team, addressing their queries, and facilitating the timely completion of their tasks. - Creating ML/Computer Vision algorithms to address specific challenges. - Analyzing and visualizing data to identify potential performance-affecting disparities in data distribution, especially when deploying models in real-world scenarios. - Establishing processes for core team operations, such as data acquisition, model training, and prototype development. - Identifying and utilizing open-source datasets for prototype building. - Developing pipelines for data processing, augmentation, training, inference, and active retraining. - Training models, fine-tuning hyperparameters, and devising strategies to address model errors. - Deploying models for production use. **Requirements:** - Bachelor's or Master's degree in Computer Science, Computer Engineering, IT, or a related field. - Minimum of 5 years of relevant experience; candidates with exceptional skills but less experience are encouraged to apply. - Industry experience in Image & Video Processing, including familiarity with OpenCV, GStreamer, TensorFlow, PyTorch, TensorRT, and various model training/inference techniques. - Proficiency in deep learning classification models (e.g., ResNet, Inception, VGG) and object detection models (e.g., MobileNetSSD, Yolo, FastRCNN, MaskRCNN). - Strong command of Pytorch, Torchvision, and the ability to develop training routines and update models effectively. - Familiarity with Colab, Jupyter Notebook, CUDA/GPU, and CNN visualization techniques like CAM and GradCAM. - Expertise in Computer Vision and real-time video processing methods. - Proficient in Python programming and adept at writing reusable code. - Experience with OpenCV, Scikit packages, NVIDIA platform tools (e.g., Deepstream, TensorRT), Python web frameworks (e.g., Flask, Django, FastAPI), and ML platforms (e.g., PyTorch, TensorFlow). - Knowledge of AWS SageMaker, various databases (e.g., Elasticsearch, SQL, NoSQL, Hive), cloud environments (preferably AWS) for software development, GPU-based training infrastructures, Docker, and DevOps and MLOps best practices for ML systems. **Desired Traits:** - Collaborative mindset and ability to thrive in a team environment. - Adaptability to evolving requirements. - Proclivity for innovative problem-solving. - Strong focus on work quality and developing robust code.,

As a Machine Learning Engineer at our company, you will be utilizing your expertise in Computer Vision, Natural Language Processing (NLP), and Backend Development. Your primary responsibilities will include developing ML/DL models for Computer Vision tasks such as classification, object detection, and segmentation, as well as for NLP tasks like text classification, Named Entity Recognition (NER), and summarization. You will also be implementing research papers and creating production-ready prototypes. To excel in this role, you must have a solid understanding of Machine Learning and Deep Learning concepts. Proficiency in tools and libraries like PyTorch, OpenCV, Pillow, TorchVision, and Transformers is essential. You will be optimizing models using techniques such as quantization, pruning, ONNX export, and TorchScript. Moreover, you will be tasked with building and deploying RESTful APIs using FastAPI, Flask, or Django, and containerizing applications using Docker for deployment on cloud or local servers. Your role will also involve writing clean, efficient, and scalable code for backend and ML pipelines. Strong backend skills using FastAPI, Flask, or Django are required, along with experience in utilizing NLP libraries like Hugging Face Transformers, spaCy, and NLTK. Familiarity with Docker, Git, and Linux environments is crucial for this position, as well as experience with model deployment and optimization tools such as ONNX and TorchScript. While not mandatory, it would be advantageous to have knowledge of Generative AI / Large Language Models (LLMs) and experience with MLOps tools like MLflow, DVC, and Airflow. Additionally, familiarity with cloud platforms such as AWS, GCP, or Azure would be a plus. The ideal candidate should hold a Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. This is a full-time position with an evening shift schedule from Monday to Friday. The work location is in person.,