Electrical Design Engineer
Translate business requirements into requirements for AI/ML models; prepare data to train and evaluate AI/ML/DL models; build AI/ML/DL models by applying state-of-the-art algorithms, especially transformers; leverage existing algorithms from academic or industrial research when applicable; test, evaluate, and benchmark the AI/ML/DL models, and publish the models, data sets, and evaluations; deploy models in production by containerizing the models; work with customers and internal employees to refine the quality of the models; establish continuous learning pipelines for models with online learning or transfer learning; build and deploy containerized applications on cloud or on-premise environments.
Machine Learning Engineer
Design, build, and maintain scalable machine learning systems including data ingestion, preprocessing, training, testing, and deployment. Develop and optimize end-to-end ML pipelines encompassing data collection, labeling, training, validation, and monitoring to ensure reliability and reproducibility. Implement robust MLOps practices such as model versioning, experiment tracking, CI/CD for machine learning, and continuous monitoring in production environments. Collaborate with product and engineering teams to integrate and deploy models into real-time products with a focus on efficiency and scalability. Ensure data quality, observability, and performance across all AI systems. Stay current with the latest AI infrastructure, tooling, and research to support ongoing innovation.
Software Engineer (SF)
Work on a small, high-caliber team building AI products for clients, from requirements gathering and prototyping through system design, development, testing, and deployment. Own features end-to-end and develop domain expertise across a range of AI use cases. Spend most of the time coding and frequently interact with clients to ensure the solutions meet their needs.
Senior / Staff Software Engineer (SF/NY)
You will work on a small, high-caliber team building AI products for clients, setting technical direction, writing code, and serving as the go-to person when challenges arise. Spend approximately 75% of your time coding and 25% interacting with clients, including CTOs, to understand problems, evaluate tradeoffs, and ensure solutions meet their needs.
Researcher, Misalignment Research
Design and implement worst-case demonstrations that concretely reveal AGI alignment risks for stakeholders, focusing on high-stakes use cases; develop adversarial and system-level evaluations based on these demonstrations and promote their adoption across OpenAI; create automated tools and infrastructure to scale automated red-teaming and stress testing; conduct research on failure modes of alignment techniques and propose improvements; publish influential internal or external papers that impact safety strategy or industry practice; collaborate with engineering, research, policy, and legal teams to integrate findings into product safeguards and governance; and mentor engineers and researchers to foster a culture of rigorous, impact-oriented safety work.
Researcher, Alignment Science
As a Research Engineer / Research Scientist on the Alignment team, you will design and implement alignment experiments focused on intent following, honesty, calibration, and robustness. You will train and evaluate models using reinforcement learning and other empirical machine learning methods. Your role includes developing evaluations for failure modes such as hallucination, instruction-following failures, reward hacking, covert actions, and scheming. You will study methods that encourage models to verify their behavior and report shortcomings honestly, including confession-style training objectives. You will build monitoring and inference-time interventions that ensure compliant behavior or surface model issues to users or downstream systems. Additionally, you will investigate how alignment methods scale with model capability, compute, data, context length, action length, and adversarial pressure. You will integrate successful techniques into model training and deployment workflows, produce externally publishable research when results advance the broader science of alignment, and collaborate with researchers and engineers across post-training, reinforcement learning, evaluations, safety, and product-facing teams.
AI/ML Engineer
Develop, train, and optimize machine learning models for various mobile app features. Research and implement state-of-the-art AI techniques to improve user engagement and app performance. Collaborate with cross-functional teams to integrate AI-driven solutions into applications. Design and maintain scalable ML pipelines, ensuring efficient model deployment and monitoring. Analyze large datasets to derive insights and drive data-driven decision-making. Stay updated with the latest AI trends and best practices and incorporate them into development processes. Optimize AI models for mobile environments to ensure high performance and low latency.
Machine Learning Enginer, Core Evaluations
The responsibilities include designing model evaluation pipelines for models in both development and production environments, designing user studies for subjective model evaluations, converting requirements into measurable metrics, and designing and developing automated evaluation dashboards to monitor and compare model performance. It also involves training new models to capture various evaluation metrics, communicating with the model team to help design improved models based on evaluation results, coordinating with the data team to determine necessary data for enhancing model performance, collaborating with the product manager to ensure product requirements are accurately measured, helping to grow the evaluation team as the founding member, and leading the evaluation team in the future.
AI/ML Engineer
Develop, train, and optimize machine learning models for various mobile app features. Research and implement state-of-the-art AI techniques to improve user engagement and app performance. Collaborate with cross-functional teams to integrate AI-driven solutions into applications. Design and maintain scalable ML pipelines, ensuring efficient model deployment and monitoring. Analyze large datasets to derive insights and drive data-driven decision-making. Stay updated with the latest AI trends and best practices, incorporating them into development processes. Optimize AI models for mobile environments to ensure high performance and low latency.
AI/ML Engineer
Develop, train, and optimize machine learning models for various mobile app features. Research and implement state-of-the-art AI techniques to improve user engagement and app performance. Collaborate with cross-functional teams to integrate AI-driven solutions into applications. Design and maintain scalable ML pipelines, ensuring efficient model deployment and monitoring. Analyze large datasets to derive insights and drive data-driven decision-making. Stay updated with the latest AI trends and best practices, incorporating them into development processes. Optimize AI models for mobile environments to ensure high performance and low latency.
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