3D Technology Lead - Research Engineer/Scientist

At World Labs, we are pioneering the development of Large World Models—advanced AI systems designed to comprehend, reason, and engage with the physical environment. Our initiatives are at the cutting-edge of spatial intelligence, robotics, and multimodal AI, with an objective to empower machines to perceive and operate effectively in intricate real-world settings.We are curating a global team of researchers, engineers, and innovators dedicated to transcending the existing boundaries of artificial intelligence. If you are eager to work on transformative technology that will redefine machine perception and enhance human-AI interaction, this role is tailored for you.About World Labs:World Labs is an AI research and development company committed to creating spatially intelligent systems capable of modeling, reasoning, and acting in the real world. We envision a future where AI transcends text or pixels to thrive in three-dimensional, dynamic environments, and we are constructing the foundational models that will make this a reality.Our team unites expertise in machine learning, robotics, computer vision, simulation, and systems engineering. We operate with the agility of a startup combined with the vision of a research lab, tackling long-term challenges that require creativity, rigor, and resilience.Our mission is to develop the most advanced world models and leverage them to empower individuals, industries, and society.Role Overview:We are seeking a Tech Lead for 3D Modeling & Reconstruction to establish technical direction and drive execution for our essential 3D modeling initiatives. This position is suited for someone with a strong background in research science (RS) or research engineering (RE) who has made significant contributions to the field of 3D reconstruction and/or modeling—evidenced by academic publications, widely adopted open-source projects, or large-scale production systems.This is a hands-on leadership role where you will merge profound technical expertise with the ability to guide a high-impact team, influencing both the research roadmap and the production systems that integrate contemporary 3D modeling techniques into tangible products. You will collaborate closely with research, engineering, and product teams to convert innovative concepts into dependable, scalable solutions.

About World Labs: At World Labs, we are at the forefront of developing foundational world models that can perceive, generate, reason, and interact with the 3D world. Our mission is to unlock the full potential of AI through spatial intelligence, transforming visual perception into actionable insights and creative output. We believe that spatial intelligence will pave the way for innovative storytelling, creativity, design, simulation, and immersive experiences in both virtual and physical realms. Our diverse team is composed of world-class professionals united by a shared passion for technology and a deep commitment to excellence. We blend expertise from AI research, systems engineering, and product design, creating a dynamic feedback loop between groundbreaking research and user-centric products. Role Overview We are seeking a dedicated 3D Reconstruction Specialist to innovate and enhance cutting-edge methodologies for reconstructing high-quality 3D geometry and appearance from real-world data. This role will primarily focus on modern reconstruction techniques—both feed-forward and optimization-based—while emphasizing novel representations, robust optimization, and scalable training and inference workflows. This is an exciting, hands-on position ideal for individuals who thrive at the intersection of computer vision, graphics, and machine learning. You will collaborate closely with research scientists, ML engineers, and product teams to translate advanced reconstruction concepts into production-ready systems that enhance our core product functionalities. What You Will Do: Design and implement state-of-the-art 3D reconstruction systems, utilizing both feed-forward and optimization-based methods for geometry, appearance, and scene comprehension. Research, prototype, and productionize advanced 3D representation techniques (e.g., implicit functions, point-based, or volumetric methods, hybrid representations) focusing on accuracy, efficiency, and scalability. Develop and refine optimization pipelines for multi-view reconstruction, including camera pose estimation, joint geometry/appearance optimization, and robust loss formulations. Create comprehensive training and evaluation workflows for 3D reconstruction models, from data preparation and supervision strategies to large-scale experiments and performance metrics. Collaborate with data and infrastructure teams to seamlessly integrate reconstruction methods with existing 3D data pipelines, rendering systems, and downstream applications. Analyze failure modes and data quality issues in real-world reconstruction scenarios, and devise principled solutions to enhance robustness and generalization.

About Our TeamJoin the Foundations Research team, where we tackle ambitious and innovative projects that could redefine the future of AI. Our mission is to enhance the science behind our training and scaling initiatives, focusing on pioneering frontier models. We are dedicated to advancing data utilization, scaling methodologies, optimization strategies, model architectures, and efficiency enhancements to accelerate our scientific breakthroughs.About the PositionWe are on the lookout for a dynamic technical research lead to spearhead our embeddings-focused retrieval initiatives. You will oversee a talented team of research scientists and engineers committed to developing foundational technologies that enable models to access and utilize the right information precisely when needed. This includes crafting innovative embedding training objectives, architecting scalable vector storage, and implementing adaptive indexing techniques.This pivotal role will contribute to various OpenAI products and internal research initiatives, offering opportunities for scientific publication and significant technical influence.This position is located in San Francisco, CA, where we embrace a hybrid work model, requiring three days in the office weekly, and we provide relocation assistance for new hires.Your ResponsibilitiesLead cutting-edge research on embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning.Supervise a team of researchers and engineers in building an end-to-end infrastructure for training, evaluating, and integrating embeddings into advanced models.Drive advancements in dense, sparse, and hybrid representation techniques, metric learning, and retrieval systems.Work collaboratively with Pretraining, Inference, and other Research teams to seamlessly integrate retrieval throughout the model lifecycle.Contribute to OpenAI's ambitious vision of developing AI systems with robust memory and knowledge access capabilities rooted in learned representations.You Will Excel in This Role If You PossessA proven track record of leading high-performance teams of researchers or engineers within ML infrastructure or foundational research.In-depth technical knowledge in representation learning, embedding models, or vector retrieval systems.Familiarity with transformer-based large language models and their interaction with embedding spaces and objectives.Research experience in areas such as contrastive learning and retrieval-augmented generation.

About the TeamJoin the innovative Post-Training team at OpenAI, where we focus on refining and elevating pre-trained models for deployment in ChatGPT, our API, and future products. Collaborating closely with various research and product teams, we conduct crucial research that prepares our models for real-world deployment to millions of users, ensuring they are safe, efficient, and reliable.About the RoleAs a Research Engineer / Scientist, you will spearhead the research and development of enhancements to our models. Our work intersects reinforcement learning and product development, aiming to create cutting-edge solutions.We seek passionate individuals with robust machine learning engineering skills and research experience, particularly with innovative and powerful models. The ideal candidate will be driven by a commitment to product-oriented research.This position is located in San Francisco, CA, and follows a hybrid work model requiring three days in the office each week. Relocation assistance is available for new employees.In this role, you will:Lead and execute a research agenda aimed at enhancing model capabilities and performance.Work collaboratively with research and product teams to empower customers to optimize their models.Develop robust evaluation frameworks to monitor and assess modeling advancements.Design, implement, test, and debug code across our research stack.You may excel in this role if you:Possess a deep understanding of machine learning and its applications.Have experience with relevant models and methodologies for evaluating model improvements.Are adept at navigating large ML codebases for debugging purposes.Thrive in a fast-paced and technically intricate environment.About OpenAIOpenAI is a pioneering AI research and deployment organization dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We are committed to pushing the boundaries of AI capabilities while prioritizing safety and human-centric values in our products. Our mission is to embrace diverse perspectives, voices, and experiences that represent the full spectrum of humanity, as we strive for a future where AI is a powerful ally for everyone.

About Our TeamJoin the forefront of AI innovation with the RL and Reasoning team at OpenAI. Our team is dedicated to advancing reinforcement learning research and has pioneered transformative projects, including o1 and o3. We are committed to pushing the limits of generative models while ensuring their scalable deployment.About the RoleAs a Research Engineer/Research Scientist at OpenAI, you will play a pivotal role in enhancing AI alignment and capabilities through state-of-the-art reinforcement learning techniques. Your contributions will be essential in training intelligent, aligned, and versatile agents that power various AI models.We seek individuals with a solid foundation in reinforcement learning research, agile coding skills, and a passion for rapid iteration.This position is located in San Francisco, CA, and follows a hybrid work model of three days in the office per week. We also provide relocation assistance for new hires.You may excel in this role if:You are enthusiastic about being at the cutting edge of RL and language model research.You take initiative, owning ideas and driving them to fruition.You value principled methodologies, conducting simple experiments in controlled environments to draw trustworthy conclusions.You thrive in a fast-paced, complex technical environment where rapid iteration is essential.You are adept at navigating extensive ML codebases to troubleshoot and enhance them.You possess a profound understanding of machine learning and its applications.About OpenAIOpenAI is a pioneering AI research and deployment organization committed to ensuring that general-purpose artificial intelligence serves the greater good for humanity. We strive to push the boundaries of AI system capabilities while prioritizing safe deployment through our innovative products. We recognize AI as a powerful tool that must be developed with safety and human-centric principles, embracing diverse perspectives to reflect the full spectrum of humanity.We are proud to be an equal opportunity employer, welcoming applicants from all backgrounds without discrimination based on race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or any other legally protected characteristic.

Join OpenAI as a Research Scientist and explore cutting-edge machine learning innovations. In this role, you will be at the forefront of developing groundbreaking techniques while advancing our team's research initiatives. Collaborate with talented peers across various teams to discover transformative ideas that scale effectively. We seek individuals who are passionate about pushing the boundaries of AI and want to contribute to our unified research vision.

AI Research ScientistAt Substrate, we are tackling a critical technological challenge that impacts the United States. Positioned at the crossroads of advanced manufacturing and innovative physics, our mission is to develop transformative technologies that will revolutionize the semiconductor industry and bolster America's technological dominance. Our team comprises top-tier scientists, engineers, and technical specialists dedicated to pushing the boundaries of technology for the benefit of the nation.As an AI Research Scientist, you will play a key role in enhancing and accelerating research and development processes by harnessing machine learning techniques for scientific simulations and modeling. You will also focus on establishing internal AI capabilities throughout our organization. This position merges cutting-edge physics with artificial intelligence, requiring hands-on development of AI-enhanced tools that facilitate groundbreaking research. You will also contribute to building the infrastructure and expertise required for our technical teams to effectively use AI in their workflows. Whether you are a physicist who has adopted machine learning or an AI expert with a solid scientific background, you will be instrumental in shaping our approach to utilizing AI to expedite our internal R&D efforts.

The Bot CompanyAt The Bot Company, we are on a mission to create a helpful robot for every home.Based in San Francisco, our small yet dynamic team comprises engineers, designers, and operators with backgrounds from industry leaders such as Tesla, Cruise, OpenAI, Google, and Pixar. Our collective experience has enabled us to deliver exceptional products to hundreds of millions of users, and we understand what it takes to create outstanding user experiences.We maintain a lean team structure to facilitate quick decision-making and eliminate the bureaucratic hurdles often present in larger organizations. Every team member is a contributor who enjoys significant autonomy, radical ownership, and direct accountability. Our culture is designed for rapid iteration and swift execution, allowing us to work across various technical stacks.Candidate ProfileWe seek candidates who possess remarkable sharpness and the capability to thrive in fast-paced, high-pressure environments. Throughout our hiring process, we look for candidates who can demonstrate:Exceptional Cognitive Abilities: You think quickly, learn rapidly, and can navigate unfamiliar domains with ease.Engineering Curiosity: You have an innate desire to understand how systems function, even beyond your area of expertise.Performance-Driven Mindset: You are agile, comfortable with ambiguity, and excel under challenging conditions.Role Overview: 3D Vision Researcher / EngineerIn this role, you will develop the 3D perception systems that enable our robots to comprehend and navigate real-world environments. We are looking for someone who can create cutting-edge 3D vision pipelines from the ground up, integrating classical geometry with modern deep learning techniques to translate research concepts into production-ready systems.

Merge Labs is an innovative research facility dedicated to merging biological sciences and artificial intelligence to enhance human capability, autonomy, and experience. Our mission is to pioneer revolutionary methodologies in brain-computer interfaces that facilitate high-bandwidth interactions with the brain, seamlessly integrate advanced AI, and maintain safety and accessibility for all users.About the TeamAt Merge, we are addressing some of the most ambitious challenges in molecular engineering, synthetic biology, and neuroscience. Our Research Platform Team is responsible for creating the experimental frameworks necessary to tackle these challenges with exceptional speed and precision. The tools and methodologies developed by our team significantly enhance molecular assembly, protein expression, mammalian cell culture, advanced microscopy, sequencing, and unique custom techniques. We collaborate with program teams to establish and optimize these capabilities, implement automation where beneficial, and integrate with our data science and machine learning pipelines, continuously pushing the boundaries of throughput and innovation.About the RoleAs a Platform Scientist, you will be instrumental in developing high-efficiency and high-throughput experimental pipelines that accelerate research initiatives. You will work closely with program leads, project scientists, data scientists, and engineers, leading your work and potentially recruiting additional team members as necessary.Key Responsibilities:Collaborate with program leads and scientists to identify critical experimental requirements and workflows.Develop processes to facilitate high-throughput and/or high-efficiency experiments, including reagent production and analysis.Scope, procure, construct, program, and validate instruments to support experimental workflows.Ensure the quality, reliability, and integrity of data generated from automated pipelines, including defining and implementing suitable quality control checkpoints.Work alongside data science and machine learning engineers to incorporate metadata tracking, computational design, and analysis into experimental pipelines.Partner with electrical, mechanical, and software engineers to create custom setups.Innovate and validate concepts to enhance experimental throughput.

OverviewBecome an integral part of our dynamic R&D team dedicated to developing fully automated research systems that push the boundaries of AI. Zochi has achieved a milestone by publishing the first entirely AI-generated A* conference paper. Locus has set a new industry standard as the first AI system to surpass human experts in AI R&D.Key ResponsibilitiesConceptualize and develop innovative architectures for automated research.Work collaboratively within a specialized team of researchers addressing cutting-edge challenges in long-horizon agentic capabilities, post-training for open-ended objectives, and environment crafting.Document and publish key internal findings alongside success stories from external collaborations.QualificationsPhD or equivalent research experience in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline. Outstanding candidates with significant research contributions are encouraged to apply, regardless of formal qualifications.Demonstrated history of impactful AI/ML research contributions in academic or corporate environments.Expertise in developing long-horizon, multi-agent systems and/or model post-training, especially in scientific domains or for open-ended discovery objectives.A strong passion for advancing problem-solving processes and scientific discovery, thriving in high-autonomy roles and environments.Our CultureCompetitive compensation and equity options.Unlimited Paid Time Off (PTO), emphasizing team collaboration and a community-focused workplace.Opportunities for conference participation and engagement in community initiatives.Empowered roles with high levels of responsibility.#1: We are a small, passionate team of leading investors, researchers, and industry experts committed to the mission of accelerating discovery. Join us.

At Scale AI, we collaborate with leading AI laboratories to supply high-quality data and foster advancements in Generative AI research. We seek innovative Research Scientists and Research Engineers with a strong focus on post-training techniques for Large Language Models (LLMs), including Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), and reward modeling. This position emphasizes optimizing data curation and evaluation processes to boost LLM performance across text and multimodal formats. In this pivotal role, you will pioneer new methods to enhance the alignment and generalization of extensive generative models. You will work closely with fellow researchers and engineers to establish best practices in data-driven AI development. Additionally, you will collaborate with top foundation model labs, providing critical technical and strategic insights for the evolution of next-generation generative AI models.

About AnthropicAt Anthropic, we are dedicated to developing AI systems that are reliable, interpretable, and steerable. We aim to ensure that AI is safe, beneficial, and aligned with the needs of both our users and society. Our expanding team consists of passionate researchers, engineers, policy experts, and business leaders collaborating to create groundbreaking AI solutions.About the RoleWe are seeking a talented Research Engineer with a solid foundation in computer vision, who shares our belief that visual and spatial reasoning are essential for unleashing the full potential of large language models (LLMs). In this collaborative role, you will engage in research, development, and evaluation of cutting-edge Claude models, with a specific emphasis on enhancing visual and spatial capabilities. You will contribute across multiple facets of our research initiatives, employing a full-stack approach that encompasses pretraining, reinforcement learning (RL), and runtime techniques such as agentic harnesses. Additionally, you will work closely with our product team to ensure that your vision enhancements positively influence Claude's performance in real-world applications.

Who We AreLightning AI, the innovative force behind PyTorch Lightning, was established in 2019 to create a seamless end-to-end platform for developing, training, and deploying artificial intelligence systems. Our mission is to facilitate the transition from research to production effortlessly.In partnership with Voltage Park, a leading neocloud and AI Factory, Lightning AI merges developer-centric software with optimized, large-scale computing solutions. We empower teams with the necessary tools for experimentation, training, and production inference while ensuring built-in security, observability, and control.We cater to individual researchers, emerging startups, and large enterprises alike. With a global presence, our offices are located in New York City, San Francisco, Seattle, and London, backed by top-tier investors including Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

About World Labs: At World Labs, we create foundational world models capable of perceiving, generating, reasoning, and interacting with the 3D environment. Our mission is to unlock the full potential of AI through spatial intelligence, transforming perception into action, reasoning into insight, and imagination into creation. We believe that spatial intelligence will revolutionize storytelling, creativity, design, simulation, and immersive experiences across both virtual and physical realms. Our world-class team is driven by curiosity and passion, boasting diverse backgrounds in technology, from AI research and systems engineering to product design. This synergy fosters a tight feedback loop between our cutting-edge research and user-empowering products. Role Overview We are seeking an innovative Research Scientist specializing in generative modeling, especially diffusion models, to join our modeling team. This position is ideal for individuals with extensive expertise in applying diffusion models to images, videos, or 3D assets and scenes. While not mandatory, experience in any of the following areas will be considered a significant advantage: Large-scale model trainingResearch in 3D computer vision In this role, you will work closely with researchers, engineers, and product teams to translate advanced 3D modeling and machine learning techniques into practical applications, ensuring our technology stays at the forefront of visual innovation. This position entails substantial hands-on research and engineering work, taking projects from conception to production deployment. Key Responsibilities Design, implement, and train large-scale diffusion models for generating 3D worlds. Develop and experiment with large-scale diffusion models to introduce novel control signals, align with target aesthetic preferences, or optimize for efficient inference. Collaborate closely with research and product teams to comprehend and translate product requirements into actionable technical roadmaps. Contribute actively to all phases of model development, including data curation, experimentation, evaluation, and deployment. Continuously investigate and integrate the latest research in diffusion and generative AI. Serve as a key technical resource within the team, mentoring peers and promoting best practices in generative modeling and machine learning engineering.

Join Our Team as a Research ScientistAt Parallel, we are at the forefront of web infrastructure innovation, enabling businesses across sectors such as sales, marketing, insurance, and technology to harness the power of AI. Our state-of-the-art products empower users to develop superior AI agents with seamless and flexible access to the web.With significant backing of $130 million from prominent investors like Kleiner Perkins, Index Ventures, and Spark Capital, we are dedicated to redefining the web for artificial intelligence. As we expand, we're assembling a top-tier team of engineers, designers, marketers, sales experts, researchers, and operational specialists committed to our vision.Your Role: As a Research Scientist, you will tackle the challenge of training and scaling models designed to enhance web indexing capabilities.About You: You possess a profound understanding of contemporary models and training methodologies. You enjoy engaging in discussions about the convergence of search, recommendations, and transformer models, and are passionate about translating your research into impactful products and systems utilized by millions.

Advancing Self-Improving SuperintelligenceAt Letta, we are on a mission to revolutionize artificial intelligence by creating self-improving agents that learn and adapt like humans. Unlike current AI systems that are often rigid and brittle, our innovative approach aims to build adaptable AI that continually evolves through experience.Founded by the visionaries behind MemGPT at UC Berkeley's Sky Computing Lab, the birthplace of Spark and Ray, we are backed by notable figures in AI infrastructure, including Jeff Dean and Clem Delangue. Our agents are already enhancing production systems for industry leaders such as 11x and Bilt Rewards, continually learning and improving in real-time.Join our elite team of researchers and engineers dedicated to tackling AI's most significant challenges: creating machines that can reason, remember, and learn as humans do.This position requires in-person attendance (no hybrid options) at our downtown San Francisco office, five days a week.

Innovating Self-Improving SuperintelligenceAt Letta, we are on a transformative journey to enhance artificial intelligence to be as adaptive and capable of learning as the human brain. Our mission is to create self-improving AI agents that continuously learn from their experiences and evolve over time.Founded by the visionary team behind MemGPT at UC Berkeley’s Sky Computing Lab—the birthplace of Spark and Ray—we are supported by industry leaders like Jeff Dean and Clem Delangue. Our cutting-edge agents are already in action at leading companies such as 11x and Bilt Rewards, improving their operations daily.Join our elite team of researchers and engineers as we tackle one of AI's greatest challenges: developing machines that can think, remember, and learn in ways similar to humans.This position is in-person (no hybrid), requiring presence 5 days a week at our downtown San Francisco office.

About Our TeamThe Future of Computing Research team is a dynamic applied research unit within the Consumer Devices group at OpenAI. We are dedicated to pioneering innovative methods, models, and evaluation frameworks that propel our vision for the future of computing. Our focus lies at the cutting edge of multimodal AI, transforming emerging model capabilities into product experiences that are not only functional and enjoyable but also foster long-term trust.Our research delves into a new generation of AI systems capable of learning and evolving over time, adapting to individual needs, and enhancing daily life. This includes exploring long-term memory, user modeling, and personalized systems aligned with broader human goals, values, and overall well-being.We collaborate closely across multiple disciplines—research, engineering, design, product management, and safety—to define what it means to build AI systems that recognize and respond to user needs in a contextually aware and respectful manner, ensuring demonstrable benefits.About the PositionWe are seeking a passionate Research Engineer/Scientist to join our Future of Computing Research team, focusing on Reinforcement Learning from Human Feedback (RLHF) and post-training techniques for personalized multimodal AI systems.In this role, you will be instrumental in establishing the learning and evaluation foundations necessary for models to become increasingly context-aware, adaptive, and useful over time. You will tackle challenges such as reward modeling, preference learning, long-horizon evaluation, and policy improvement for systems that are required to make high-quality behavioral decisions in real-world settings. Our success is measured not just by improved benchmark performance but by enhanced model behavior in actual use cases.The ideal candidate is enthusiastic about advancing beyond simplistic one-turn assistant interactions towards systems that learn and grow through feedback, utilizing richer signals and training against meaningful notions of user value. This requires a thoughtful approach to reward design, feedback mechanisms, and evaluation frameworks that assess the long-term benefits of interventions.This position is based in San Francisco, CA, with a hybrid work model of four days in the office each week. We also provide relocation assistance for new hires.Key Responsibilities:Develop RLHF and post-training strategies for multimodal models.Create reward models and preference-learning pipelines to foster adaptive, personalized model behavior.Engage in long-term evaluation and policy refinement to enhance user interactions.

About UsAt Preference Model, we are pioneering the development of next-generation training data that drives the future of artificial intelligence. While current models demonstrate significant capabilities, they often fall short in diverse applications due to many tasks being out of distribution. We create reinforcement learning environments where models tackle real-world research and engineering challenges, continuously iterating and learning from authentic feedback loops.Our founding team, with experience from Anthropic’s data division, has built the infrastructure and datasets that support the Claude AI. We collaborate with top-tier AI laboratories to accelerate AI's journey toward its transformative potential, and we are proudly backed by a16z.About the RoleWe envision a future where models can autonomously train on their weaknesses. We seek innovative thinkers eager to explore the limits of self-directed learning. In this position, you will meld research with engineering, implementing cutting-edge methodologies and influencing research trajectories.Representative Projects:Architect and enhance our core reinforcement learning infrastructure, developing clean training abstractions and distributed experiment management systems to accommodate increasingly complex research workflows.Design, implement, and validate training environments, evaluations, and methodologies for reinforcement learning agents.Enhance performance through profiling, optimization, and benchmarking. Implement efficient caching techniques and debug distributed systems to expedite training and evaluation processes.Collaborate with cross-functional teams in research and engineering to establish automated testing frameworks, design user-friendly APIs, and build scalable infrastructure that propels AI research forward.You May Be a Good Fit If You:Are proficient in Python and familiar with frameworks like PyTorch or Jax.Have hands-on experience in training and conducting machine learning research on large language models.Can effectively balance research exploration with practical engineering implementation.Enjoy pair programming and prioritize code quality, testing, and performance.Possess strong systems design and communication skills.Have a solid understanding of reinforcement learning algorithms and stay updated with current publications in the field.

About Scale AI At Scale AI, we are committed to propelling the advancement of AI technologies. For over eight years, we have been a pioneer in the AI data sector, supporting groundbreaking innovations in areas such as generative AI, defense solutions, and autonomous driving. Following our recent Series F funding round, we are enhancing access to premium data to accelerate the journey towards Artificial General Intelligence (AGI). Building on our legacy of model evaluation for both enterprise and governmental clients, we are expanding our capabilities to establish new benchmarks for evaluations in both public and private domains. About This Role This position is at the leading edge of AI research and practical implementation, concentrating on reasoning within large language models (LLMs). The successful candidate will investigate critical data types vital for evolving LLM-based agents, including browser and software engineering agents. You will significantly influence Scale’s data strategy by pinpointing optimal data sources and methodologies to enhance LLM reasoning. To excel in this role, you will require a profound understanding of LLMs, planning algorithms, and fresh approaches to agentic reasoning, alongside inventive solutions to challenges in data generation, model interaction, and evaluation. Your contributions will lead to transformative research on language model reasoning, facilitate collaboration with external researchers, and engage closely with engineering teams to translate cutting-edge advancements into scalable, real-world applications.