Member of Technical Staff, Robotics Research Lead
Lead the design and execution of the AI’s robotics research agenda, recruit, mentor, and manage a small team of research scientists and engineers in the London lab, collaborate with the world model and simulation teams to develop state-of-the-art training platforms for robotics, guide the creation of persistent 3D/4D scene representations and advanced embodied AI methodologies, drive research efforts in scene understanding, sim-to-real transfer, and advanced planning, foster partnerships with leading ML researchers, hardware specialists, and external collaborators, and help establish the lab's technical culture and external reputation.
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.
Machine Learning Research, RF Foundation Models Specialist
Formulate new machine learning problems in RF sensing and spectrum understanding. Design experiments and evaluation approaches reflecting real operating conditions such as domain shift, changing interference, and varying sensors and platforms. Build models for structured, noisy, and partially observed signal environments. Improve robustness across propagation, interference, and low-visibility waveform conditions. Optimize models for throughput, latency, and deployment constraints. Move promising research into a release path for real systems through proofs-of-concept, realistic validation, and conversion into maintainable, deployable code. Use field performance to inform the development of the next generation of models and tooling. Work across the lifecycle of research and deployment including data and evaluation design, experimentation, model development, release readiness, and iteration based on real-world outcomes. Collaborate closely with embedded, hardware, and mission teammates, influencing how machine learning capability is built as the company scales.
Researcher, Agentic Post-Training
Own end-to-end research and engineering projects to improve the final post-training of OpenAI’s agentic models. Decide which integrations are ready for inclusion in major model runs in collaboration with partner teams. Develop horizontal model improvements in areas such as factuality, instruction following, tool/function calling, multi-agent behavior, and reasoning-effort calibration. Build and improve training, evaluation, grading, and data infrastructure for large-scale reinforcement learning/post-training runs. Create evaluations and diagnostics to assess model readiness for deployment. Enhance feedback loops from real product usage into post-training, including learning from implicit user feedback. Collaborate with Codex, API, ChatGPT, product, training, and other post-training teams to make frontier models more useful, reliable, and agentic.
Staff Research Engineer
As a Staff Research Engineer at Decagon, you will lead research and engineering efforts to improve core conversational capabilities in production, including instruction following, retrieval, memory, and long-horizon task completion. You will build and iterate on end-to-end models and pipelines that optimize for quality, efficiency, and user experience. You will partner with platform and product engineers to integrate new models into production systems. Responsibilities also include breaking down ambiguous research ideas into clear, iterative milestones and roadmaps, mentoring other researchers and engineers, setting technical direction, and establishing best practices for applied research and engineering.
Senior Research Engineer
As a Senior Research Engineer, you will lead research and engineering efforts to improve core conversational capabilities in production including instruction following, retrieval, memory, and long-horizon task completion. You will build and iterate on end-to-end models and pipelines that optimize for quality, efficiency, and user experience. You will partner with platform and product engineers to integrate new models into production systems. Additionally, you will break down ambiguous research ideas into clear, iterative milestones and roadmaps.
Clinician Scientist
Develop and refine AI-driven clinical tools across notes, risk adjustment (HCC capture), clinical decision support, and prior authorization using clinical expertise and prompt engineering; define what "clinically meaningful" output looks like for each product area, including acceptable error rates, failure modes, and quality thresholds; collaborate with cross-functional teams including engineers, data scientists, and clinicians to integrate medical insights into AI models; write, review, and optimize prompts to improve AI model performance in clinical contexts; build and refine evaluation tools to streamline medical documentation quality assessment including hallucination detection, omission detection, and medication safety checks; translate clinical needs into technical specifications and data models; define clinical guardrail metrics and baselines and own pre/post evaluation requirements for any model update that affects clinical output; contribute to product development, revenue cycle management, and broader business initiatives; monitor clinical guideline update cycles and flag when product behavior needs to evolve based on new standards or payer policies.
Graduation Internship - AI Research - Paris
Participate in research and development within the Models team, Data Research team, or Agent team in H Company's research lab as a graduation internship; work on building foundational models powering agentic technology, advancing multimodal intelligence through large-scale models, and defining new learning algorithms and agent paradigms for autonomous AI systems.
PhD Research Intern, Vision Language Action Models
Work on the Multimodal Language Action model by exploring novel discrete action tokenization and flow matching approaches, building on MotionLM, FAST, and other models. Train models at the billion+ scale using millions of miles of proprietary Zoox driving data. Gain experience and insight into training Multimodal Language Action models at scale. Contribute to publishable research that could be integrated into Zoox vehicles.
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