About UsAt Cohere, our mission is to amplify intelligence to benefit humanity. We specialize in training and deploying cutting-edge models for developers and enterprises, enabling them to create extraordinary AI experiences such as content generation, semantic search, retrieval-augmented generation (RAG), and intelligent agents. Our work is pivotal in driving the widespread adoption of artificial intelligence.We are deeply passionate about our creations. Each team member plays a crucial role in enhancing our models and maximizing the value they deliver to our clients. We thrive on hard work and agility, always prioritizing the needs of our customers.Cohere is made up of a diverse team of leading researchers, engineers, designers, and more, all dedicated to their craft. We value unique perspectives as essential for developing exceptional products.Join us in our journey to shape the future of AI!Role OverviewAs Large Language Models (LLMs) redefine the capabilities of AI, inference remains a critical bottleneck. Our Model Efficiency team is at the forefront of enhancing LLM inference efficiency across our foundational models. We focus on groundbreaking advancements in the model execution stack, encompassing:Optimization of model architecture and mixture of experts (MoE) routingInnovations in decoding and inference-time algorithmsCo-design of software and hardware for GPU accelerationPerformance enhancements without sacrificing model qualityNote: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul, and London. We embrace a remote-friendly culture, strategically distributing teams based on interests, expertise, and time zones to foster collaboration and flexibility. Our Model Efficiency team primarily operates in the EST and PST time zones.As a Staff Research Engineer, you'll be instrumental in developing, prototyping, and deploying methodologies that significantly enhance the speed and efficiency of our models in production.Ideal Candidate ProfileYou may be an excellent fit for our Model Efficiency team if you:Hold a PhD in Machine Learning or a closely related disciplinePossess a deep understanding of LLM architecture and optimization techniques for inference under resource constraintsBring substantial experience in model optimization and performance enhancement strategies

About BasisBasis is a nonprofit organization dedicated to applied artificial intelligence research. Our mission is twofold: to understand and build intelligence and to advance society’s problem-solving capabilities. We strive to unravel the mathematical principles behind reasoning, learning, decision-making, understanding, and explanation, while also developing software that embodies these principles.Our commitment extends to enhancing our ability to tackle complex issues that are beyond today's capabilities and accelerating our potential to address future challenges. We are creating a technological framework inspired by human reasoning, alongside fostering a collaborative organization that prioritizes human values.About the RoleAs a Research Scientist, you will spearhead Basis’ initiatives to deepen our understanding of the conceptual, mathematical, and computational principles of intelligence. We seek individuals who excel technically and are passionate about exploring foundational concepts. Our research team values rigorous, high-quality scientific endeavors while encouraging experimentation and exploration of innovative ideas.Basis thrives on collaboration, both internally and with external partners. We are looking for team players who enjoy tackling significant problems that require collective effort.Research FocusDespite the growing acknowledgment that acquiring and understanding world models is crucial for intelligence, current AI systems face challenges in mirroring this human capability. Key uncertainties remain regarding the essence of a world model, methods for reliably detecting its presence in agents, and approaches to develop agents capable of learning these models effectively.Our research, particularly within the MARA project, seeks to establish new foundations and technologies for modeling, abstraction, and reasoning in AI systems. MARA's goal is to identify principled methods for how intelligence constructs, refines, and employs world models through interactive experimentation. Achieving this will require advancements in knowledge representation, abstraction, reasoning, active learning, and reinforcement learning, necessitating a first-principles reevaluation of world modeling.

About UsAt Cohere, we're on a mission to harness and scale intelligence for the betterment of humanity. We specialize in training and deploying cutting-edge models for developers and enterprises, enabling them to create transformative AI experiences such as content generation, semantic search, retrieval-augmented generation (RAG), and intelligent agents. We are committed to fostering the widespread adoption of AI technologies.Our passion for excellence drives us to continuously enhance our models and the value they deliver to our clients. We thrive in a fast-paced environment where hard work and innovation are paramount to achieving the best outcomes for our users.Cohere is made up of a diverse team of researchers, engineers, designers, and more, all of whom are leaders in their fields. We believe that a variety of perspectives is essential to creating outstanding products.Join us in our quest to shape the future!Role OverviewOur rapidly expanding team of researchers and engineers is dedicated to building robust machine learning systems and enhancing the efficiency of large language model (LLM) inference. We focus on developing innovative techniques that improve production execution of models, resulting in reduced latency, increased throughput, and consistent performance across various workloads.As a member of this team, you will engage with the inference stack to enhance key performance metrics by analyzing model execution, identifying performance bottlenecks, and crafting pioneering optimizations. You will work closely with both modeling and systems teams to test, measure, and implement enhancements that significantly improve inference speed. As the team progresses, you will have the chance to deepen your knowledge in advanced performance techniques, including GPU/CUDA optimizations, kernel-level enhancements, and execution strategies for mixture of experts (MoE) and large-scale architectures.Note: Cohere has offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul, and London. We embrace a remote-friendly approach, strategically distributing teams based on interests, expertise, and time zones to enhance collaboration and flexibility. The Model Efficiency team is primarily based in the EST and PST time zones.Who You Are5+ years of experience coding high-performance, production-level softwareProficient in C++ or Python (experience in Rust/Go is also a plus)Strong understanding of machine learning concepts and frameworksExperience in optimizing ML systems for production environmentsExcellent problem-solving skills and ability to collaborate effectively in a team setting

Role overview Decagon seeks a Staff Research Engineer based in New York City. This position helps guide research efforts and supports the development of technical solutions that serve a range of industries. The Staff Research Engineer works alongside a skilled team, taking projects from early ideas through to working implementations. What you will do Advance research initiatives at Decagon through direct engineering contributions Collaborate with team members to design and build new technical solutions Apply technical expertise to projects that impact several sectors Requirements Solid background in both research and engineering Interest in tackling complex technical problems Strong collaborator who values team-based problem solving

About UsAt Percepta, we are on a mission to revolutionize pivotal industries through applied AI. Our focus is on ensuring that the sectors that drive our world, including healthcare, manufacturing, and energy, harness the power of cutting-edge technology. To achieve this, we closely collaborate with top-tier clients to facilitate AI transformation. We unite:Expertise in engineering, product, and research that is deployed at the forefront of innovation.Mosaic, our proprietary toolkit designed for the rapid implementation of intelligent workflows.Strategic alliances with leading firms such as Anthropic, McKinsey, AWS, and others within the General Catalyst portfolio.Our team consists of a dynamic group of Applied AI Engineers, Embedded Product Managers, and Researchers who are passionate about integrating AI to enhance everyday experiences. Percepta is a proud partner of General Catalyst, a global leader in transformation and investment.Role OverviewAs a Research Engineer/Scientist specializing in LLM Modeling at Percepta, you will be at the forefront of developing and deploying large-scale language models. You will engage in pre-training, post-training (including instruction tuning, alignment, and distillation), reinforcement learning, and the crafting of specialized architectures to enhance reasoning, decision-making, and adaptability across critical sectors.Collaboration is key as you will work closely with Embedded Product Managers and engineers to create innovative yet practical decision systems that significantly transform business operations.Identify significant challenges and formulate research strategies encompassing pre-training, post-training, RL, and specialized model development.Prototype and scale training pipelines for large language models, experimenting with architectures, optimization methods, and post-training tactics.Contribute to the infrastructure necessary for high-performance distributed training.Conduct extensive real-world evaluations that yield millions in value.Collaborate with applied AI engineers to transition successful research findings into actionable features within our Mosaic platform.Effectively communicate research outcomes to both technical and non-technical stakeholders, ensuring clarity on the implications of research and its applications.

About BasisBasis is a pioneering nonprofit organization specializing in applied AI research, dedicated to two interrelated goals.The primary objective is to comprehend and develop intelligence. This entails establishing the mathematical foundations of reasoning, learning, decision-making, understanding, and explanation; as well as creating software that embodies these principles.The secondary goal is to enhance society's capacity to tackle complex challenges. This involves broadening the scale and complexity of the problems we can address today and, more importantly, accelerating our future problem-solving capabilities.To realize these ambitions, we are constructing a new technological base inspired by human reasoning and fostering a collaborative organization that prioritizes human values.About the RoleAs a Research Engineer in Operations at Basis, you will be instrumental in developing internal tools, automation, and measurement systems that significantly enhance researcher productivity and operational efficiency. Your work will involve creating tools that eliminate hours of manual tasks, automating proposal and CRM workflows, and offering analytics to guide strategic decisions as Basis expands.We seek individuals who are technically adept and possess a deep understanding of research workflows, enabling them to pinpoint high-impact automation opportunities. An ideal candidate has experience in converting research concepts into reliable code, building automation systems powered by LLMs, and designing user-friendly tools for researchers. Your contributions will range from researcher productivity enhancements to GTM automation and analytics infrastructure.This position is vital to Basis's growth strategy, transforming operations from manual to automated processes that facilitate scalable growth with sustainable results.We are looking for innovative thinkers who are technically accomplished and eager to explore foundational concepts. Our research engineers strive to develop high-quality, robust tools, unafraid to experiment, learn from mistakes, and explore unconventional ideas to achieve their goals.Basis thrives on collaboration, both internally and with our partners; we seek individuals who are passionate about empowering others to achieve milestones they couldn't accomplish alone.

About Mirage Mirage builds an AI-powered video platform that connects production and editing through natural language processing. Our models use contextual awareness to mirror the choices of skilled editors, streamlining workflows for experienced teams and making video creation more accessible to a wider audience. Learn More Our Product (Captions by Mirage) Our Research (Seeing Voices, technical white paper) Latest Updates (Mirage on X / Twitter) Mirage has been featured in TechCrunch, Forbes AI 50, and Fast Company. Our Investors Mirage is backed by leading venture firms and entrepreneurs, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, and others. Location Requirement All roles at Mirage require in-person work at our Union Square headquarters in New York City. Role Overview: Research Engineer – Large Language Models Mirage seeks a Research Engineer to design, build, and scale systems for training and deploying large language models, with a focus on multimodal creative applications in video analysis. This role works closely with researchers to turn new ideas into efficient, production-ready systems that strengthen our platform.

At CVector, we are dedicated to revolutionizing economic optimization and AI-driven predictions across energy and manufacturing sectors. Our vision is to empower industrial facilities to make informed decisions every minute, balancing cost, reliability, and margin through a unified decision-making layer that seamlessly integrates real-time asset constraints with market dynamics.This pivotal role is based in our New York City office, where our team collaborates four days a week to deliver solutions to clients across the country, operating in demanding industrial environments.Position OverviewThe Senior Research Engineer plays a crucial role in enhancing our modeling, analysis, and machine learning capabilities, enabling our clients to meet their economic, operational, and sustainability objectives. These modeling frameworks are essential to the functionality of CVector's AI Agents, ensuring customers receive precise and actionable insights based on real-world equipment and facility constraints.Reporting directly to the Chief Technology Officer, you will architect and implement models and analytical tools tailored for both standardized products and unique customer requirements. Your responsibilities will include the development and deployment of CVector's techno-economic analysis (TEA) and linear programming (LP) models, guiding clients on optimizing their operations for greater profitability, minimized energy expenses, and reduced emissions. Additionally, you will engage with our extensive library of machine learning and AI algorithms for time series analysis, anomaly detection, forecasting, and predictive maintenance.This role is perfect for a seasoned energy modeler or data scientist with a robust background in the energy or industrial sectors. We are looking for an individual who thrives in a dynamic startup atmosphere and enjoys collaborative efforts that engage founders, investors, clients, and team members alike.Key ResponsibilitiesEnhance CVector's modeling and analysis framework to support and improve the AI Agent experience.Integrate market data APIs for real-time insights on energy and commodity prices, carbon intensity, and weather forecasts.Apply various time series analysis techniques, leveraging AI/ML methodologies for energy forecasting and predictive maintenance.Utilize our algorithm training architecture to ensure high-quality results for our customers.Develop and implement techno-economic analysis (TEA) and linear programming (LP) models to optimize operations.Prepare and present TEA and LP model outcomes to clients, shaping their operational strategies.

About BasisBasis is a pioneering nonprofit organization dedicated to applied AI research, driven by dual objectives that enhance each other.Our primary focus is to understand and construct intelligence. This encompasses establishing the fundamental mathematical principles of reasoning, learning, decision-making, comprehension, and explanation, alongside developing software that embodies these principles.Secondly, we aim to empower society to tackle complex challenges. This involves broadening the scale, complexity, and scope of problems we can currently address and, crucially, accelerating our future problem-solving capabilities.To realize these ambitions, we are establishing an innovative technological framework inspired by human reasoning and fostering a collaborative environment that prioritizes human values.About the RoleAs a Research Engineer, you will play a vital role in advancing Basis’ mission by converting research concepts into accurate, robust, and scalable high-quality code.We are looking for technically proficient individuals who are enthusiastic about delving deep into foundational concepts. Our research engineers are committed to conducting rigorous, high-quality science, unafraid to experiment, learn from mistakes, and explore innovative ideas.Basis thrives on collaboration, both within our team and with external partners. We seek individuals who enjoy tackling challenges greater than they can manage alone.Machine Learning Research Engineer Focus AreasThis position is aimed at experts in machine learning engineering. Key areas of focus include:Probabilistic programming and statistical inferenceDeep learningCausal inferenceProgram synthesis and analysisML Ops and systems engineeringThese areas will be explored in the context of developing reasoning systems. Research engineers will also engage with topics including programming language design and implementation, automatic differentiation, and SAT/SMT solvers.

About General IntuitionGeneral Intuition is at the cutting edge of AI research, dedicated to developing foundational models that excel in deep spatial and temporal reasoning. Over the past year, we have advanced the capabilities of AI agents that navigate complex environments, created world models that serve as training grounds for these agents, and innovated video understanding models aimed at real-world application.We are proud to have raised a seed funding round of $133 million from General Catalyst and Khosla, driving our mission to uncover the next generation of intelligence.What We're Looking ForMinimum of 5 years of experience in deep learning research or reinforcement learning, specifically with embodied agents or simulation environments.Solid foundation in representation learning and generative modeling, particularly using architectures like diffusion models, VAEs, and transformers applied to video data.Experience with world models and predictive control — you possess knowledge on training models that simulate dynamics and plan actions within learned environments.Proficiency in reinforcement learning (RL, model-based RL, or imitation learning), coupled with the capability to design and evaluate policy networks.Excellent programming skills in Python and deep learning frameworks such as PyTorch.Strong experimental capabilities — adept in handling large-scale training, evaluation pipelines, and managing intricate datasets or simulations.Publications or contributions to open-source projects in domains such as world modeling, simulation learning, or agent policies are a significant advantage.In-person requirement: We are specifically seeking candidates located in New York City, with a commitment to working in the office five days a week.Ownership & scientific rigor: You are committed to seeing ideas through from conception to proof of concept to deployment. You write clean, reproducible code and uphold high standards for experimental validity.Performance and scaling mindset: You understand how research can be translated into production systems, with a keen awareness of compute efficiency, distributed training, and potential data bottlenecks.Curiosity-driven and results-oriented: You thrive on tackling open-ended problems, while also knowing how to set measurable goals and deliver impactful systems.Passion for gaming & simulation: A strong interest in interactive environments and physics-based simulations is highly desirable.

About BasisBasis is a pioneering nonprofit organization focused on applied AI research, driven by dual objectives.Our first goal is to comprehend and construct intelligence. We endeavor to lay down the mathematical principles defining reasoning, learning, decision-making, understanding, and explanation, while also developing software that embodies these principles.The second aim is to enhance society's capability to tackle complex challenges. We strive to broaden the scale, complexity, and diversity of problems we can address today, and more critically, to hasten our capacity to resolve future challenges.To fulfill these ambitions, we are creating an innovative technological foundation inspired by human reasoning, alongside a collaborative organization that prioritizes human values.About the RoleAs a Data Engineer on the Platform team at Basis, you will be responsible for constructing reliable data pipelines featuring comprehensive provenance and quality controls. You will curate documented datasets for training and evaluation while ensuring that our data infrastructure scales effectively. Your work will encompass both platform-specific data needs and cross-project data coordination, minimizing redundancy and fostering shared datasets.We are in search of technically proficient individuals who regard data quality as paramount. The ideal candidate has experience with machine learning data pipelines, understands the complete lifecycle from raw data to model training and evaluation, and approaches data provenance, lineage tracking, and quality assurance with rigor. You will blend software engineering best practices with a profound understanding of data systems and machine learning requirements.This role operates across both the Platform and Research teams, working on infrastructure that supports our commercial offerings and internal research initiatives. You will play a vital role in scaling Basis's data operations to support medium-scale models, ensuring data governance as we cater to external clients, and building systems that researchers can rely on for reproducible experiments.We seek individuals who are committed to executing high-quality, robust data engineering while remaining open to iteration, learning from real-world usage, and exploring diverse approaches to achieve excellence.At Basis, collaboration is key—both internally and with our external partners. We value those who enjoy laying the groundwork for solving grand challenges that extend beyond individual efforts.

Bravos Research stands at the forefront of investment research and financial media, specializing in video-first content. Our mission is to empower investors with insightful, data-driven research to navigate the complexities of global markets.As the proud creator of the largest investment research channel on YouTube, we have amassed over 75 million views and a substantial subscriber base for our premium research services.We are on the lookout for a Senior Research Analyst who can merge institutional-level macroeconomic insights with captivating storytelling. In this role, you will transform intricate economic data into engaging narratives and manage the end-to-end research and scriptwriting process for our animated videos, focusing on US and global macro trends, liquidity, credit markets, commodities, and cryptocurrencies.Key Responsibilities:Produce high-conviction insights regarding global business cycles, equity markets, central bank policies, and asset allocation strategies.Craft compelling, thoroughly sourced scripts that simplify complex economic concepts for a broad audience without compromising depth.Collaborate with team members to establish the firm's investment strategy and overarching perspectives.

About UsMirror Physics is an innovative AI company based in New York City, pioneering the next generation of scientific simulation technologies. Our mission is to create intelligent systems that grasp the fundamental principles of physics, thereby providing essential acceleration for advanced research and development across various technological fields. We are currently developing a leading-edge AI platform that predicts experimental outcomes in chemistry and materials science, seamlessly integrating physical simulation with high-throughput experimental verification. This endeavor aims to hasten discoveries in biotechnology, energy, manufacturing, and more. Supported by top-tier investors and scientific experts, we are seeking to expand our research team during this crucial period in the industry.The RoleAs the principal AI researcher focusing on physics model development, you will lead efforts in designing innovative architectures, training algorithms, and evaluation processes to transform vast amounts of physical simulation data into scalable, precise, and versatile predictive engines applicable in both scientific and industrial contexts.Key ResponsibilitiesCreate robust, scalable, and universally applicable atomistic models with high fidelity across various chemical domains.Compile diverse and multi-fidelity datasets into cohesive training corpora; innovate new objectives to enhance data efficiency.Produce groundbreaking datasets that encompass an unmatched variety of chemical systems, consistently computed at the highest theoretical levels suitable for general chemistries.Design diagnostic tools for model performance evaluation, failure mode assessment, and uncertainty quantification; propose new benchmarks to rigorously test predictive accuracy, physical consistency, and extrapolation capabilities.Develop downstream tools to improve model precision and processing speed, including model distillation and fine-tuning techniques.Collaborate with the AI-for-science community through research publications and contributions at leading conferences such as NeurIPS, ICML, and ICLR.Mentor junior researchers and work closely with applied science and engineering teams.

About UsAt Cohere, our vision is to enhance intelligence to better serve humanity. We specialize in training and deploying cutting-edge models for developers and enterprises, enabling them to create extraordinary AI-driven experiences such as content generation, semantic search, retrieval-augmented generation (RAG), and intelligent agents. Our work is pivotal in fostering the broad acceptance of AI technologies.We are deeply passionate about our creations. Each team member plays a vital role in enhancing the capabilities of our models and delivering exceptional value to our clients. We prioritize hard work and agility to ensure we meet our customers' needs effectively.Cohere comprises a diverse team of researchers, engineers, designers, and other professionals who are dedicated to their craft. Our collective expertise is among the best globally, and we believe that a variety of perspectives is essential for developing outstanding products.Join us to be a part of this transformative journey!About This PositionWe are seeking a seasoned machine learning researcher or engineer to help us explore and advance the realm of agentic large language model (LLM) systems. In this role, you will spearhead the exploration and development of innovative agentic techniques, and you will have the chance to create models that drive our agentic solutions. Agentic LLM systems are increasingly being adopted by enterprises through Cohere’s North platform. Your contributions will focus on developing novel strategies for training models that enhance agent capabilities, including reasoning, tool usage, and memory management. This involves creating data generation methods for post-training enhancements (Supervised Fine-Tuning and Reinforcement Learning). The advancements made in model development will have direct implications for North and other Cohere offerings, presenting an exciting opportunity where foundational model innovations translate into significant product improvements.Please note: Our offices are located in London, Toronto, San Francisco, and New York, and we embrace a remote-friendly work culture! We prefer candidates based in Eastern Time, but remote or hybrid arrangements are welcome.Your Responsibilities as a Member of Technical Staff for Agents Modeling:Design and develop innovative agentic solutionsEnhance state-of-the-art performance on challenging agentic tasksInvestigate next-generation online learning-from-experience techniques for self-improvementCollaborate with cross-functional teams (Reasoning, Post-training, Pre-training, etc.) to boost the performance of agentic systemsCollaborate with an exceptional team of researchers and engineers...

About BasisBasis is a nonprofit organization dedicated to applied AI research, striving to achieve two interconnected objectives.Firstly, we aim to understand and develop intelligence. This involves establishing the mathematical foundations of reasoning, learning, decision-making, comprehension, and explanation; along with creating software that embodies these principles.Secondly, we seek to enhance society's capacity to address complex challenges. This means broadening the range, scale, and intricacies of the problems we can tackle today, while also accelerating our ability to solve future challenges.To fulfill these missions, we are constructing a novel technological framework inspired by human reasoning, and fostering a collaborative organization that prioritizes human values.About the RoleAs a Research Scientist, you will spearhead Basis's initiatives to deepen our comprehension of the theoretical, mathematical, and computational aspects of intelligence.We seek individuals with exceptional technical skills who are passionate about exploring concepts at their core. Our research scientists and engineers are committed to conducting rigorous, high-quality, and robust scientific inquiry, yet they embrace experimentation, learning from mistakes, and exploring innovative ideas to achieve their goals.Basis thrives on collaboration, both internally and with external partners; thus, we value team players who relish tackling challenges that surpass individual capabilities.Research FocusOur research under the MARA project is dedicated to forging new principles and technologies for modeling, abstraction, and reasoning in AI systems. The primary aim of MARA is to reveal principled methodologies for how intelligence constructs, refines, and applies world models through interactive experimentation.For this position, we specifically seek experts in Reinforcement Learning & Planning who can push the boundaries of model-based RL, exploration strategies, optimal control, and Bayesian optimization. You will develop agents capable of learning efficient policies in intricate, partially observable environments by utilizing structured world models.

Mirage builds an AI-native platform for video production and editing, centered in Union Square, New York City. The platform uses natural language to guide intelligent orchestration, allowing advanced models to understand context and mimic the creative decisions of experienced editors. This approach aims to boost productivity for professional teams and open up video creation to a wider audience. About the Team The team at Mirage brings together people from a range of backgrounds, blending technical and artistic skills to solve tough challenges in generative media. The work goes beyond routine model development, focusing on problems that remain unsolved across the industry. Role Overview: Research Scientist, Large Language Models This early team role offers the chance to shape the core technology behind Mirage. The position involves tackling foundational questions in generative AI and creative tooling, with the potential to influence how people create and edit video for years to come.

Role overview Distributed Spectrum is seeking a Machine Learning Research Specialist to advance research on RF Foundation Models. The focus of this position is on developing new machine learning methods that support radio frequency communications. What you will do Lead research into machine learning techniques tailored for RF communications. Create and evaluate new data-driven models to enhance connectivity. Work closely with colleagues who combine expertise in machine learning and radio frequency technology. The team Distributed Spectrum’s team investigates innovative approaches to connectivity and communication. Their projects push the boundaries of what is possible in machine learning and RF signal processing. Location This position is located in New York City.

About the FellowshipThis prestigious Postdoctoral Fellowship at Basis Research offers a unique opportunity to collaborate with the renowned Ellis Lab at Cornell University. As a fellow, you will play a vital role in the groundbreaking MARA project, focused on the development of foundational AI technologies. This initiative aims to empower systems to actively discover abstract models of the world and utilize them for effective reasoning to achieve their objectives.About BasisBasis is a nonprofit organization dedicated to applied AI research, striving to accomplish two interrelated goals. The first goal is to understand and construct intelligence, establishing the mathematical principles behind reasoning, learning, decision-making, understanding, and explanation, while developing software that embodies these principles. The second goal is to enhance society’s capacity to tackle complex challenges, expanding the scale and complexity of problems we can address today, and accelerating our ability to solve future challenges. To achieve these objectives, we are building a new technological foundation inspired by human reasoning, along with a collaborative organization that prioritizes human values.About Kevin Ellis’ GroupUnder the leadership of Kevin Ellis, Assistant Professor in the Computer Science department at Cornell University, the Ellis Lab conducts research in artificial intelligence, program synthesis, and the intersection of AI and cognitive science. The lab explores methodologies for constructing AI systems that learn and reason akin to human cognition, emphasizing areas such as programming by example, world modeling, neural-symbolic integration, and few-shot learning. By integrating techniques from machine learning, program synthesis, probabilistic programming, and cognitive science, the group aims to develop AI systems capable of learning intricate tasks from minimal data and generalizing across various domains.Research FocusOur research is centered on establishing new foundations and technologies for modeling, abstraction, and reasoning within AI systems, with a primary focus on the MARA project. The overarching goal of MARA is to create systems that actively discover abstract representations of the world and utilize these representations to accomplish specific objectives. Achieving this will require significant advancements in knowledge representation, abstraction techniques, and reasoning methodologies.

Role overview Jobgether seeks a Chief of Staff for its Research & Development team. This remote position partners with executive leadership to guide and support major initiatives within the R&D organization. The Chief of Staff coordinates projects, helps improve how the team operates, and plays a key part in meeting organizational goals. What you will do Partner with R&D leadership to move strategic projects and priorities forward Streamline daily operations across the R&D department Assist with project management so teams stay aligned and on schedule Encourage a culture that values innovation and high standards Location This position is remote and based in New York.