3 Scalable Tools Jobs

Accenture is a global professional services company with leading capabilities in digital, cloud, and security across more than 40 industries. The company offers Strategy and Consulting, Technology and Operations Services, and Accenture Song powered by the world's largest network of Advanced Technology and Intelligent Operations centers. With 699,000 employees serving clients in over 120 countries, Accenture embraces the power of change to create value and shared success for clients, people, shareholders, partners, and communities. As a Data Science Consultant in the Financial Services - Banking practice of Accenture Strategy & Consulting Global Network, based in Mumbai, you will work at the core of clients" organizations to address complex issues in the financial services industry. Your expertise in industry, management, and technology will provide critical solutions to strategic, operational, technology, and sourcing demands, contributing to the future of the global financial services industry. You will have the opportunity to be part of a diverse and vibrant global Accenture data science community, continually expanding analytical capabilities, working with top financial clients globally, and developing new skills within functional and technical areas. Additionally, you will have access to resources enabling you to leverage the latest technologies and drive innovation with leading companies worldwide. In this role, your responsibilities will include: Client Engagement: - Collaborating closely with clients to understand their business goals and challenges. - Developing data & AI strategies aligned with business objectives and industry best practices. - Collaborating with business stakeholders to comprehend analytical requirements and deliver actionable insights. Data Analysis and Modeling: - Applying statistical and machine learning techniques to analyze large datasets. - Designing, developing, testing, and implementing solutions based on business requirements and strategic direction. - Performing data testing to ensure adherence to internal processes, policies, and regulatory guidelines. - Developing predictive models and algorithms to extract valuable insights. ML Ops: - Designing data pipelines and engineering infrastructure to support enterprise machine learning systems. - Translating offline models into real machine learning production systems. - Developing and deploying scalable tools and services for machine learning training and inference. - Identifying and evaluating new technologies to enhance performance, maintainability, and reliability of machine learning systems. Join Accenture as a Data Science Consultant to drive innovation, deliver strategic solutions, and shape the future of the financial services industry.,

As a Deep Learning Engineer, you will be responsible for utilizing cutting-edge Deep Learning techniques to develop advanced algorithms for neural rendering using Python and popular deep learning frameworks. You will collaborate closely with a team of passionate researchers and developers to address complex challenges in deep learning, including multi-modal image synthesis, audio-visual data fusion, and image/video transformation. Your role will involve enhancing the performance of products to ensure high levels of accuracy, speed, and scalability, with guidance from senior team members. Additionally, you will integrate developed software, algorithms, and AI models into our products and services, working collaboratively with stakeholders. It will be your responsibility to maintain the software's security, reliability, and maintainability, following the guidance of senior team members. You will be required to conduct thorough testing and validation to meet the desired performance standards. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Engineering, or a related field. You should have at least 3 years of industry or research experience in deep learning and computer vision, focusing on areas such as computational photography, neural talking head synthesis, representation and synthesis of lifelike facial attributes, and video synthesis. Experience with self-supervised, few-shot, or zero-shot learning techniques for image synthesis, as well as domain adaptation techniques for face image synthesis, is highly desirable. Moreover, you should have a strong understanding of Generative networks for use-cases like Super-resolution, In painting, etc., and state-of-the-art deepfake algorithms. A minimum of 2 years of relevant experience with generative networks like Transformers, GANs, Auto-encoders, Diffusion models, etc., and at least 1-year experience with Vision Transformers is required. Experience with multi-modal image synthesis with audio-visual data and proficiency in Python programming and deep learning frameworks like PyTorch or TensorFlow are essential, with a minimum of 3 years of experience. Furthermore, experience in developing scalable tools and solutions for real-world computer vision problems or visual effects, exceptional problem-solving skills, and the ability to work effectively in a team environment are crucial for this role. Candidates with an MS or Ph.D. in Visual Computing, Computer Vision, Machine Learning, or a related field, as well as experience with 3D GANs for human body/face synthesis, will be considered a bonus.,

Utilize cutting-edge deep learning techniques to develop advanced algorithms for neural rendering using Python and popular deep learning frameworks. Collaborate closely with a team of passionate researchers and developers to address complex challenges in deep learning, including multi-modal image synthesis, audio-visual data fusion, and image/video transformation. Enhance the performance of products, ensuring high levels of accuracy, speed, and scalability, with guidance from senior team members. Integrate developed software, algorithms, and AI models into our products and services, working collaboratively with stakeholders. Maintain the software's security, reliability, and maintainability, following senior team members" guidance. Conduct thorough testing and validation to meet the desired performance. Requirements: - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - 3+ years of industry or research experience in deep learning and computer vision, focusing on areas such as computational photography, neural talking head synthesis, representation and synthesis of lifelike facial attributes, and video synthesis. - Experience with self-supervised, few-shot, or zero-shot learning techniques for image synthesis, as well as domain adaptation techniques for face image synthesis. - Strong understanding of Generative networks for various use-cases like Super-resolution, Inpainting, etc., and state-of-the-art deepfake algorithms. - Minimum 2 years of relevant experience with generative networks such as Transformers, GANs, Auto-encoders, Diffusion models, etc. - Minimum 1-year experience with Vision Transformers. - Experience with multi-modal image synthesis with audio-visual data. - Proficiency in Python programming and deep learning frameworks like PyTorch or TensorFlow, with at least 3 years of experience. - Experience in developing scalable tools and solutions for real-world computer vision problems or visual effects. - Exceptional problem-solving skills and the ability to work effectively in a team environment. Bonus Qualifications: - MS or Ph.D. in Visual Computing, Computer Vision, Machine Learning, or a related field. - Experience with 3D GANs for human body/face synthesis.,