2 Openai Gpt4O Jobs

At PwC, the focus is on leveraging data to drive insights and make informed business decisions in the field of data and analytics. The team utilizes advanced analytics techniques to help clients optimize their operations and achieve strategic goals. As a Data Analyst at PwC, your role will involve utilizing advanced analytical techniques to extract insights from large datasets and facilitate data-driven decision-making. Your responsibilities will include data manipulation, visualization, and statistical modeling to support clients in solving complex business problems. With a minimum of 12 years of hands-on experience, you will be responsible for designing and implementing scalable, secure, and high-performance architectures for Generative AI applications. This involves integrating Generative AI models into existing platforms, fine-tuning pre-trained generative models for domain-specific use cases, and developing strategies for data collection, sanitization, and preparation. You will also be evaluating, selecting, and deploying appropriate Generative AI frameworks such as PyTorch, TensorFlow, Crew AI, Autogen, Langraph, Agentic code, and Agentflow. Staying abreast of the latest advancements in Generative AI and recommending innovative applications to solve complex business problems is crucial. You will define and execute the AI strategy roadmap, identifying key opportunities for AI transformation. Collaboration with cross-functional teams, mentoring team members on AI/ML best practices, and making architectural decisions are essential aspects of the role. Monitoring the performance of deployed AI models and systems, optimizing computational costs, and ensuring compliance with ethical AI practices and data privacy regulations are key responsibilities. Safeguards must be implemented to mitigate bias, misuse, and unintended consequences of Generative AI. Required skills for this role include advanced programming skills in Python, proficiency in data processing frameworks like Apache Spark, knowledge of LLMs foundational models, experience with event-driven architectures, familiarity with Azure DevOps and other LLMOps tools, expertise in Azure OpenAI Service and vector DBs, containerization technologies like Kubernetes and Docker, comprehension of data lakes and data management strategies, proficiency in cloud computing platforms like Azure or AWS, exceptional leadership, problem-solving, and analytical abilities, superior communication and collaboration skills, and the ability to operate effectively in a dynamic environment. Nice-to-have skills include experience with technologies like Datadog and Splunk, possession of relevant solution architecture certificates, and continuous professional development in data engineering and GenAI. A professional and educational background in any graduate / BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA is required for this role.,

At PwC, the focus is on leveraging data to drive insights and make informed business decisions in the field of data and analytics. Utilizing advanced analytics techniques, you will assist clients in optimizing their operations and achieving strategic goals. As a data analyst at PwC, your primary tasks will involve extracting insights from large datasets and facilitating data-driven decision-making. Your role will require skills in data manipulation, visualization, and statistical modeling to help clients solve complex business problems effectively. With a minimum of 12 years of hands-on experience, the responsibilities associated with this position include: Architecture Design: - Designing and implementing scalable, secure, and high-performance architectures for Generative AI applications. - Integrating Generative AI models into existing platforms, focusing on compatibility and performance optimization. Model Development and Deployment: - Fine-tuning pre-trained generative models for domain-specific use cases. - Developing data collection, sanitization, and data preparation strategies for model fine-tuning. - Evaluating, selecting, and deploying appropriate Generative AI frameworks like PyTorch, TensorFlow, Crew AI, Autogen, Langraph, Agentic code, and Agentflow. Innovation and Strategy: - Staying updated with the latest advancements in Generative AI to recommend innovative applications for solving complex business problems. - Defining and executing the AI strategy roadmap while identifying key opportunities for AI transformation. Collaboration and Leadership: - Collaborating with cross-functional teams, including data scientists, engineers, and business stakeholders. - Mentoring and guiding team members on AI/ML best practices and architectural decisions. Performance Optimization: - Monitoring the performance of deployed AI models and systems to ensure robustness and accuracy. - Optimizing computational costs and infrastructure utilization for large-scale deployments. Ethical and Responsible AI: - Ensuring compliance with ethical AI practices, data privacy regulations, and governance frameworks. - Implementing safeguards to mitigate bias, misuse, and unintended consequences of Generative AI. Required Skills: - Advanced programming skills in Python with fluency in data processing frameworks like Apache Spark. - Strong knowledge of LLMs foundational models and open-source models like Llama 3.2, Phi, etc. - Proven track record with event-driven architectures and real-time data processing systems. - Familiarity with Azure DevOps and LLMOps tools for operationalizing AI workflows. - Deep experience with Azure OpenAI Service, vector DBs, API integrations, prompt engineering, and model fine-tuning. - Knowledge of containerization technologies such as Kubernetes and Docker. - Comprehensive understanding of data lakes and data management strategies. - Expertise in LLM frameworks including Langchain, Llama Index, and Semantic Kernel. - Proficiency in cloud computing platforms like Azure or AWS. - Exceptional leadership, problem-solving, and analytical abilities. - Strong communication and collaboration skills with experience managing high-performing teams. Nice to Have Skills: - Experience with additional technologies such as Datadog and Splunk. - Possession of relevant solution architecture certificates and continuous professional development in data engineering and GenAI. Professional and Educational Background: - Any graduate/BE/B.Tech/MCA/M.Sc/M.E/M.Tech/Masters Degree/MBA.,