AI Research Scientist
The AI Research Scientist is responsible for designing, training, and optimizing machine learning models including large language models, multimodal models, transformers, and diffusion architectures. They conduct research on model efficiency, quantization, compression, and on-device deployment, prototype novel model architectures, training methods, and inference strategies for distributed AI. They also develop and evaluate benchmarks, datasets, and experimental frameworks to test model performance, collaborate with engineering teams to integrate research findings into production systems, stay current on leading research in deep learning, generative AI, and distributed ML, analyze experimental results and communicate insights to technical and non-technical stakeholders, document research findings, contribute to internal papers, present technical work across the organization, and identify emerging technologies to propose research directions aligned with company strategic priorities.
Research Scientist
The Research Scientist will engage in hands-on technical work across all phases of research projects, from early exploration to developing working prototypes for real-world applications. They will take a leadership role in identifying promising AI applications relevant to the company's mission, formulate and advocate for research programs, and drive impactful initiatives. Collaboration with cross-functional teams to share research findings, advocate for their practical use, and guide productization efforts is required. Additionally, the role includes documenting experimental results, contributing to peer-reviewed publications, participating in patenting innovations, and mentoring junior researchers to help them develop their independent research and communication skills.
Research Scientist
Work on solving scientific challenges related to Conversational AI to build domain-specific, real-world solutions. Engage in hands-on technical work in all aspects of research projects from early exploration to working prototypes to achieve successful real-world applications. Identify promising applications of AI relevant to ASAPP’s core mission, formulate and advocate for research programs in those areas, and take ownership of driving impactful research initiatives. Collaborate with cross-functional teams to socialize research findings, advocate for their application, and guide the productization of those findings to improve customer experience solutions. Document significant experimental results, contribute to publishing peer-reviewed papers, and participate in patenting innovations. Mentor and guide junior researchers, helping them develop their skills in independent research and communication of their findings.
Member of Technical Staff - Evaluations
Conduct critical comparative analysis to advance understanding of model capabilities. Build and refine evaluation systems and processes that create tight feedback loops between data, evaluations, and model behavior. Develop generalizable evaluation frameworks that capture what matters for reasoning, alignment, and usefulness. Collaborate closely with pre-training, post-training, and applied teams to translate insights into model improvements. Push the boundaries of what is measurable, including synthetic evaluations, human feedback, and real-world interaction data.
Early Career Program
As an Applied Research Scientist at Superhuman, the core responsibilities include developing state-of-the-art tools for correcting, improving, and enhancing written English using various NLP, ML, and DL technologies. The role requires productizing and shipping these features into Superhuman's product offerings used by millions daily. The individual must stay up-to-date with the latest research trends that could enhance the product, contribute to the research strategy and technical culture of the company, and help attract professionals in the industry to build a best-in-class research team that creates state-of-the-art writing and communication assistants. Additionally, the position involves contributing to ideation and defining solution spaces based on a deep understanding of ML/DL/NLP concepts and building intelligent functionality in the company's product offerings.
Staff ML Research Scientist (Clinical)
Lead high-impact machine learning research projects from concept to deployment focused on clinical NLP and reasoning systems. Define the technical direction of research initiatives within product areas by identifying opportunities to apply state-of-the-art models to real-world radiology workflows. Collaborate with radiologists and clinical experts to understand diagnostic reasoning patterns, report structures, and clinical decision-making criteria, then encode that understanding into robust ML systems. Architect and evaluate models integrating structured and unstructured medical data to enhance diagnostic reasoning and reporting accuracy. Build NLP systems capable of parsing, reasoning over, and generating clinically accurate content using medical terminology and ontologies. Mentor and guide other researchers in experimental design, model reproducibility, and technical communication. Contribute to advancing research infrastructure, including data pipelines, training frameworks, and model evaluation tooling.
Senior+ AI Researcher (Large Language Models)
Lead research on large language models (LLMs) and vision-language models (VLMs) for conversational avatars, focusing on modeling both verbal and non-verbal interactions. Design and implement fine-tuning, adaptation, and conditioning techniques to control LLM behavior and align it with real-world conversational needs. Prototype, train, and optimize models capable of operating in real-time generation settings with time budget constraints. Collaborate with applied machine learning and product teams to transition research into impactful production systems. Mentor other researchers, set research directions, and foster scientific excellence.
Machine Learning Scientist - NLP
Experiment with and develop machine learning algorithms specific to use cases in agentic AI, LLMs, and traditional ML models. Develop evaluation frameworks, submit scientific reports to conferences, and collaborate with product and engineering teams to implement high-impact AI solutions.
Research Staff, Voice AI Foundations
As a Member of the Research Staff, the role involves pioneering the development of Latent Space Models (LSMs) to address data, scale, and cost challenges in voice AI. Responsibilities include building next-generation neural audio codecs for low bit-rate compression and high fidelity reconstruction of general audio, pioneering steerable generative models for diverse human speech synthesis, developing embedding systems to factorize codec latent space into interpretable dimensions allowing controlled manipulation and amplification of seed datasets, leveraging latent recombination to generate synthetic audio data at large scales, designing multimodal speech-to-speech systems capable of universal human understanding and producing human-like responses, and designing model architectures, training schemes, and inference algorithms adapted for hardware to enable cost-efficient training on billion-hour datasets and power real-time inference for massive concurrent conversations.
Research Engineer/Research Scientist, RL
As a Research Engineer/Research Scientist at OpenAI, the role involves advancing the frontier of AI alignment and capabilities through cutting-edge reinforcement learning (RL) methods. The work centers on training intelligent, aligned, and general-purpose agents, including the systems powering various models. Responsibilities include pushing the boundaries of reinforcement learning research, building next-generation generative models, deploying them at scale, iterating quickly in a fast-paced and technically complex environment, and debugging and improving a large machine learning (ML) codebase.
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