4 Image Synthesis Jobs

As a GenAI Model Developer, your role will involve building and deploying GenAI Models using techniques such as RAG and Fine Tuning. You will be responsible for developing AI/ML algorithms to analyze large volumes of historical data in order to make predictions and recommendations. Additionally, you will implement and optimize deep learning models for generative tasks like image synthesis and voice applications. Collaboration with software engineers to integrate Generative AI models into production systems will be a key aspect of your role. You should be able to evaluate application cases and the problem-solving potential of AI/ML algorithms, ranking them according to their likelihood of success. This will involve comprehending data through exploration and visualization, as well as identifying discrepancies in data distribution. Working with both structured and unstructured data, you will develop various algorithms based on statistical modeling procedures and build scalable machine learning solutions for production. Leveraging cloud platforms for training and deploying large-scale solutions, with a preference for AWS, will also be part of your responsibilities. You should have a working knowledge of managing the ModelOps framework and understand CI/CD processes for product deployment. Collaborating with data engineers to build data and model pipelines, ensuring accuracy, will be essential. You are expected to take complete ownership of assigned projects and have experience working in Agile environments. Proficiency in tools such as JIRA or equivalent project tracking tools is required to succeed in this role.,

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.,

At PwC, our data and analytics team focuses on utilizing data to drive insights and support informed business decisions. We leverage advanced analytics techniques to assist clients in optimizing their operations and achieving strategic goals. As a data analysis professional at PwC, your role will involve utilizing advanced analytical methods to extract insights from large datasets, enabling data-driven decision-making. Your expertise in data manipulation, visualization, and statistical modeling will be pivotal in helping clients solve complex business challenges. PwC US - Acceleration Center is currently seeking a highly skilled MLOps/LLMOps Engineer to play a critical role in deploying, scaling, and maintaining Generative AI models. This position requires close collaboration with data scientists, ML/GenAI engineers, and DevOps teams to ensure the seamless integration and operation of GenAI models within production environments at PwC and for our clients. The ideal candidate will possess a strong background in MLOps practices and a keen interest in Generative AI technologies. With a preference for candidates with 4+ years of hands-on experience, core qualifications for this role include: - 3+ years of experience developing and deploying AI models in production environments, alongside 1 year of working on proofs of concept and prototypes. - Proficiency in software development, including building and maintaining scalable, distributed systems. - Strong programming skills in languages such as Python and familiarity with ML frameworks like TensorFlow and PyTorch. - Knowledge of containerization and orchestration tools like Docker and Kubernetes. - Understanding of cloud platforms such as AWS, GCP, and Azure, including their ML/AI service offerings. - Experience with continuous integration and delivery tools like Jenkins, GitLab CI/CD, or CircleCI. - Familiarity with infrastructure as code tools like Terraform or CloudFormation. Key Responsibilities: - Develop and implement MLOps strategies tailored for Generative AI models to ensure robustness, scalability, and reliability. - Design and manage CI/CD pipelines specialized for ML workflows, including deploying generative models like GANs, VAEs, and Transformers. - Monitor and optimize AI model performance in production, utilizing tools for continuous validation, retraining, and A/B testing. - Collaborate with data scientists and ML researchers to translate model requirements into scalable operational frameworks. - Implement best practices for version control, containerization, and orchestration using industry-standard tools. - Ensure compliance with data privacy regulations and company policies during model deployment. - Troubleshoot and resolve issues related to ML model serving, data anomalies, and infrastructure performance. - Stay updated with the latest MLOps and Generative AI developments to enhance AI capabilities. Project Delivery: - Design and implement scalable deployment pipelines for ML/GenAI models to transition them from development to production environments. - Oversee the setup of cloud infrastructure and automated data ingestion pipelines to meet GenAI workload requirements. - Create detailed documentation for deployment pipelines, monitoring setups, and operational procedures. Client Engagement: - Collaborate with clients to understand their business needs and design ML/LLMOps solutions. - Present technical approaches and results to technical and non-technical stakeholders. - Conduct training sessions and workshops for client teams. - Create comprehensive documentation and user guides for clients. Innovation And Knowledge Sharing: - Stay updated with the latest trends in MLOps/LLMOps and Generative AI. - Develop internal tools and frameworks to accelerate model development and deployment. - Mentor junior team members and contribute to technical publications. Professional And Educational Background: - Any graduate / BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA,

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.,