Model Policy Manager
Design model policies that govern safe model behavior in an objective and defensible way, determining how models should respond in risky or unsafe scenarios and defining what unsafe means while balancing safety with beneficial model capabilities. Develop taxonomies that guide data collection campaigns, model behavior, and monitoring strategies, balancing maximizing utility with preventing catastrophic risk. Lead prioritization efforts for safety across the company related to new model launches, addressing technical and business trade-offs. Develop broad subject matter expertise while maintaining agility across various topics. Collaborate across many internal teams, requiring high organizational acumen and confident decision making.
Head of Clinician Science
Lead and grow the Clinician Science team by recruiting, developing, and managing clinician scientists with diverse specialty expertise, while fostering a culture of clinical rigor, intellectual curiosity, and cross-functional collaboration. Ensure clinical excellence across product development by partnering with product teams to embed clinical expertise into feature discovery, design, and validation, translating clinical workflows and best practices into actionable product requirements. Define and uphold clinical quality standards by establishing frameworks for what "clinically meaningful" means across specialties, note types, and workflows, and guide the team in evaluating note quality, prompt iterations, and model outputs through LFD sessions and systematic assessments. Build scalable clinical evaluation systems by partnering with ML Science to develop LLM judges, annotation frameworks, and evaluation pipelines that scale clinical expertise and ensure evaluation methodologies reflect real-world clinical judgment. Serve as a translator between clinical reality and ML/engineering capabilities to help both engineers and clinicians understand respective nuances and constraints. Close the feedback loop with Commercial by partnering with Clinical Success and Solutions Consulting to surface real-world usage insights, customer feedback, and quality issues, ensuring product development stays grounded in how clinicians actually use Abridge. Represent the clinical perspective in Builder strategy by participating in roadmap planning, feature prioritization, and cross-pod alignment discussions, acting as the voice of clinical credibility in product decisions.
PhD Research Intern (Measurement and Evaluation)
Design and conduct evaluations of Abridge models and products; develop a strong user-centric and patient-centric mindset, grounding the research in empathy for the real world experience of providers and patients; collaborate across cross-functional product teams to ensure the research is deeply informed by current practices and the product roadmap; write technical reports and give presentations to internal stakeholders; receive mentorship from the Head of Strategic Research.
Staff Research Engineer, Voice
As a Staff Voice Research Engineer, you will lead the development of models and algorithms powering Decagon's real-time voice agents and manage multi-quarter initiatives to improve speech understanding, naturalness, turn-taking, and resilience in real-world conditions. Responsibilities include leading research and engineering efforts to enhance core conversational capabilities such as instruction following, retrieval, memory, and long-horizon task completion; building and iterating on end-to-end models and pipelines to optimize quality, efficiency, and user experience; partnering with platform and product engineers to integrate new models into production systems; 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.
Staff Research Engineer
As a Staff Research Engineer at Decagon, you will be responsible for building industry-leading conversational AI models that power Decagon’s agent, taking them all the way from idea to production. You will own multi-quarter initiatives that enhance the agent’s reliability, capability, and efficiency. Your responsibilities include leading research and engineering efforts to improve core conversational capabilities in production such as instruction following, retrieval, memory, and long-horizon task completion. You will build and iterate on end-to-end models and pipelines optimizing for quality, efficiency, and user experience. Additionally, you will partner with platform and product engineers to integrate new models into production systems. You will break down ambiguous research ideas into clear, iterative milestones and roadmaps. You will also mentor other researchers and engineers, set technical direction, and establish best practices for applied research and engineering.
Technical Program Manager, R&D & Technology Transfer
Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control by designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. Collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities deployable on physical hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms for high precision manipulation of complex or deformable objects. Work with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.
Research Engineer/Scientist - Generative UI, Consumer Products
As a Research Engineer/Scientist on the Consumer Products Research team, you will train and evaluate state-of-the-art models along important axes for future devices, work through challenges to transform nascent research capabilities into usable capabilities, and help define software frameworks for long-term future use.
Senior Research Engineer/Scientist - Edge, Consumer Products
As a Research Engineer/Scientist on the Consumer Products Research team, you will train and evaluate multimodal state-of-the-art (SoTA) models along axes important to the vision for future devices. You will develop novel architectures that improve model performance when scaling the models themselves is not an option. You will also work to transition nascent research capabilities into capabilities that can be built upon.
Researcher, Preparedness
The responsibilities include owning the scientific validity of frontier preparedness capability evaluations by designing new evaluations based on real threat models in high-consequence domains such as CBRN and cyber risks, maintaining existing evaluations to prevent staleness or regression, defining datasets, graders, rubrics, and threshold guidance, and producing auditable artifacts such as evaluation cards, capability reports, and system-card inputs to support leadership decisions during high-stakes launches. Other tasks involve identifying emerging AI safety risks and new methodologies to explore their impact, building and refining evaluations of frontier AI models to assess these risks, designing and building scalable systems and processes that support these evaluations, and contributing to risk management refinement and development of best practice guidelines for AI safety evaluations.
Senior Operations Manager - Supply Partnerships
The role involves conducting original research in collaboration with Snorkel researchers on open-ended projects, producing clear research outputs such as experiments, prototypes, internal writeups, and potentially publications depending on fit and timing. Responsibilities include innovating Human-AI Interaction by designing new paradigms for distilling human expertise into model behavior, defining frontier capabilities by collaborating with leading labs to develop data strategies for next-generation agentic, reasoning, and multi-modal models, and producing real business impact within fast cycles. Example project areas include synthetic data generation and filtering for specialized tasks, creating evaluation datasets and benchmarks for LLM, RAG, and agent behavior, developing data-centric methods to improve reliability, calibration, and failure-mode coverage, and evaluating human-in-the-loop data annotation processes, gaps, and improvements.
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