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About The Team The Data Understanding team is responsible for creating the high quality datasets and their quantized representation for OpenAI. This includes synthesizing data, building VQ representations, and processing, filtering, deduplication, quality control, and tokenization so it can be used effectively in big model training runs. About The Role We're looking to advance how OpenAI builds and understands pretraining data at scale. You'll treat data quality and curation as core research problems: developing new methods to select, combine, and transform data; creating datasets that improve model capabilities; and designing rigorous experiments to understand how data choices and interventions affect model learning and downstream behavior. You'll work closely with frontier models and web-scale data to build evidence for which approaches work and why, then translate successful research into scalable data processing pipelines We Expect You To Have a strong track record of new or improved ML ideas, through publications, projects, or applied research. Own and drive a research agenda, from choosing the right problems to carrying long-running work through to impact. Be excited by OpenAI’s empirical, collaborative approach to research. Nice To Have Thoughtfulness about AI’s impact, including privacy, provenance, and data quality. Experience building high-performance deep learning or large-scale data processing systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a researcher focused on our embedding retrieval efforts. You’ll work with a a team of world-class research scientists and engineers developing foundational technology that enables models to retrieve and condition on the right information, at the right time. This includes designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods. This work will support retrieval across many OpenAI products and internal research efforts, with opportunities for scientific publication and deep technical impact. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Responsibilities Tackle embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning. Collaborate with a team of researchers and engineers building end-to-end infrastructure for training, evaluati

About The Team The Data Understanding team is responsible for creating the high quality datasets and their quantized representation for OpenAI. This includes synthesizing multimodal data, building VQ representations, and processing, filtering, deduplication, quality control, and tokenization so it can be used effectively in big model training runs. About The Role We’re looking to advance how OpenAI prepares, curates, synthesizes and understands multimodal data at scale. You’ll work on research and production problems like synthesizing multimodal content (images, audio, and video) and their supervisions, improving noisy data pipelines, building better quality filters, using models to automate data prep, and measuring whether changes in the dataset improve model performance. We Expect You To Have a strong track record of new or improved ML ideas, through publications, projects, or applied research. Own and drive a research agenda, from choosing the right multimodal data problems to carrying long-running work through to impact. Be excited by OpenAI’s empirical, collaborative approach to research. Nice To Have Experience with multimodal learning, audio, vision, video, synthetic data, or data-centric ML. Thoughtfulness about AI’s impact, including privacy, provenance, and data quality. Experience building high-performance deep learning or large-scale data processing systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of

About the Team The Recursive Self-Improvement (RSI) team works across research, engineering, product, and infrastructure to build AI systems that accelerate and ultimately conduct high-quality research at OpenAI. We work to automate real research workflows and improve research productivity by building systems and feedback loops, designing evaluations, and training models to develop missing capabilities. Our work spans the full lifecycle of model training, evaluation, and deployment to help researchers move faster and tackle increasingly ambitious problems. About the Role We’re hiring research scientists , research engineers , and AI systems engineers to work on automating research at OpenAI. This role is based in San Francisco, CA. In this role, you will: Design evaluations for research judgment, hypothesis generation and testing, and long-horizon experiment execution. Turn real research workflows and model failures into data and evaluation flywheels. Improve model research capabilities through agent harnesses, synthetic data, RL environments, and model training. Build and maintain safe, reliable integrations between our models and OpenAI’s research infrastructure. Develop research agents, experiment-orchestration systems, and sandboxed runtimes that support real research workflows. Create metrics and economic models to understand RSI’s current and future effects on research productivity, model capabilities, and the safety of internal deployments. This is a high-ownership role for researchers and engineers who thrive in ambiguity, move fluidly between research and implementation, and turn emerging opportunities into rigorous, reliable, scalable results. You might thrive in this role if you: Have research or engineering experience across LLM training, model evaluations, agent systems, synthetic data, research infrastructure, or large-scale distributed systems. Are a strong generalist who can move between open-ended research and practical implementation, turning ambig

Job Title Remote Service Engineer, IGT-S (Remote-Based) Job Description Exciting opportunity combine your technical, networking, and customer interaction skills utilizing the latest remote access technologies to assist healthcare customers with IGT - Fixed Systems products. Your role: Acting as a Remote Service Engineer (RSE), the aim of your job is to provide telephone, remote technical support, and remote diagnostics to external healthcare customers and field partners, utilizing the latest remote access technologies. Acting as a Philips Representative in response to customer inquiries and providing telephone and remote technical support to external customers Resolving customer service events by leveraging Philips tools and resources as needed Timely escalation of customer product issues for evaluation and action by higher level support Utilization of appropriate remote tools to resolve issue and thus avoid dispatching of service call to Field Service Engineer Implementing best practices and process improvements while diagnosing problems, apply effective solutions and determine follow up actions Driving increased productivity through utilization of remote tools and technical skills Responds to customer product inquiries via telephone or in written internet-based email or chat sessions. Interpersonal skills and technical product knowledge and expertise are critical to responding to daily customer-centric activities. You're the right fit if: You’ve acquired 2+ years of experience in a diagnostic imaging (field or hospital-based) service environment. Philips Image Guided Therapy (IGT) System - Azurion and/or Alllura systems experience and training is required. Your skills include the ability to understand and apply electronic, mechanical