CVPR 2025 Career Opportunities

Los Altos, CA

At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team in Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics.

THE CHALLENGE

The long-term vision of TRI’s Accelerated Materials Design and Discovery (AMDD) program is to accelerate the development of truly emissions-free mobility. Realizing this vision will require the discovery of new materials and devices for batteries, fuel cells, and more. Our aim at TRI is to merge sophisticated computational materials modeling, new experimental data, artificial intelligence, and automation to significantly accelerate materials research. Our focus is on developing tools and capability to enable this acceleration. We collaborate closely with colleagues across global Toyota, as well as with universities and national labs. AMDD seeks to develop and translate the newest technologies into practice, both within Toyota and the open research community.

THE OPPORTUNITY

This role is based at our headquarters in Los Altos, CA. We are offering a Postdoctoral Researcher position for individuals who have recently completed their PhD and are ready to conduct cutting-edge research with real-world impact. This is a one-year appointment with an option to extend another year by mutual agreement. We are looking for researchers who want to learn about and tackle problems related to the scientific design of energy materials. Currently, we need to bridge the gap between simulation and experiment. You will help incorporate scientific theory or intuition into new machine learning models that provide actionable input for materials design in labs, not just on computers. You will collaborate with software engineers and researchers to translate your work into prototype tools, and gain scientific insights through Toyota-focused and open projects. This is a unique opportunity to contribute to cutting-edge research and deepen your knowledge of the AI for Materials landscape.

THE TEAM

You will expand your professional network, as part of a creative team of scientists and engineers dedicated to enabling a sustainable future. Our team prioritizes learning new skills together at the interface of materials science and AI. You will be part of the Energy & Materials division which is accelerating Toyota’s path to carbon neutrality. In addition to our work on accelerating materials discovery, the division develops capabilities for battery manufacturing and provides strategic analysis on carbon neutral pathways and technologies.

Qualifications

• Have completed a PhD in the past three years in a related STEM field.

• Have a strong research background, including peer-reviewed publications, in the areas of materials informatics, computational workflows, lab automation, synthesis, electrochemistry, catalysis, batteries, fuel cells, and/or AI.

• Are proficient with Python.

• Are excited by the prospect of translating fundamental research into practical, human-centered tools that address real-world industrial problems.

• Thrive in a culture that values diversity, collaboration, humility, and learning.

Please add a link to Google Scholar and include a full list of publications when submitting your CV to this position.

Los Altos, CA

At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built world-class teams in Human-Centered AI, Energy & Materials, Human Interactive Driving, Large Behavioral Models, and Robotics.

TRI’s Harmonious Communities Department within our Human-Centered AI (HCAI) Division has an immediate opening for a Staff AI Research Scientist interested in our core topic domain of social well-being and the future of work. We are looking for someone with expertise in and enthusiasm for machine learning research (e.g., model architecting, simulations, complex datasets).

We are particularly keen to talk with people who have interest or experience in using real-world, human-level data to model prefactuals and counterfactuals (e.g., multi-agent-based modeling, reinforcement learning, causal inference + ML, RDM + AI, Graph Neural Networks). We are launching a new project space, and want a colleague who can help define and build this trajectory.

Our mission is to use research to foster Toyota’s global mission of “wellbeing and happiness for all,” and this challenge motivates everything we do. We are a coordinated team of behavioral scientists, ML researchers, and human-computer interaction experts. The person who accepts this opportunity must have a strong interest in collaborating across all of these domains. Additionally, this role will work with teams across Toyota to design and pilot technologies that help us to better understand the social dynamics within and around our workplaces. Candidates should be self-starting and interested in making contributions within a multidisciplinary team project.

Responsibilities

• Collaborate cross-functionally with specialists in multiple fields, as well as university partners, to research and develop technology that models emergent properties in social systems.

• Stay current on the state-of-the-art in Machine Learning theories, practice, and software.

• Collaborate with scientists in the Harmonious Communities Department to shape and craft our research program and to communicate research to Toyota collaborators and stakeholders.

• Publish findings in academic journals and/or conferences (e.g., KDD, ICWSM, WWW, ACL, EMNLP, NAACL, AAMAS, CSCW).

• Contribute to technology transfer of research throughout Toyota.

Qualifications

• 7+ years of experience with PhD in computer science, machine learning, computational social science, or related field, with a broad knowledge of machine learning approaches and theory. We encourage candidates to apply even if they don’t meet every qualification. We value diverse experience and are open to learning more about how your unique skills could contribute to the team.

• Experience with simulation / prefactual / counterfactual approaches (multi-agent-based modeling, GNNs, Robust Decision Modeling + AI, etc.).

• Experience with architecting ML systems across diverse data sources (text, time-series data, tabular data, etc.), including familiarity with cloud platforms (AWS, GPC, or Azure), virtualization (Docker), and orchestration (Kubeflow, Metaflow).

• Proficiency in ML frameworks (e.g. scikit-learn, PyTorch, TensorFlow, Keras), and tools for big data analysis (e.g. Databricks, Sagemaker, SQL, Spark).

• Ability to communicate complex concepts clearly across different audiences.

• Strong interpersonal skills, enthusiastic collaborator, and great teammate.

• Heavy interest in research to facilitate social wellbeing.

Los Altos, CA

At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team in Human-Centered AI, Human Interactive Driving, Energy and Materials, Machine Learning, and Robotics.

The Human Interactive Driving team seeks to accelerate the path to building a much more intelligent vehicle that places humans at the center of a more evocative and safer driving experience. Under the Driving-Sensei concept, we research AI-based interactions to unlock a person’s full driving capability while simultaneously making driving safer and more enjoyable.

We are looking for a software engineer to join the Human Machine Interaction Research (HMIR) team to work on our Driving-Sensei project. You’ll collaborate closely with multi-functional teams, spanning AI research, UX design, and vehicle systems engineering. You will translate future-facing research into integrated, testable, and demonstrable HMI experiences within real vehicle prototypes and development platforms. This role is instrumental in owning and delivering our full HMI application—from early research integration to end-to-end performance, stability, and usability within experimental vehicle platforms.

Responsibilities

• Be responsible for the full lifecycle of the HMI application, from architectural design and software integration to performance tuning and in-vehicle validation.

• Specify and implement a full stack SW architecture that integrates vehicle telemetry data, human-machine interface (HMI) hardware (physiological sensing, touch displays, audio, AR headsets), machine learning (ML) models, LLMs, and 2D UIs.

• Work closely with vehicle HW engineers to integrate SW architecture onto vehicles.

• Collaborate with front-end SW engineers and designers to integrate UX code into the system.

• Integrate and modify existing research code that comprise key components of the system.

• Lead the effort to coordinate and restructure research code into modular, stable and well-documented functions.

• Establish continuous integration, test, and deployment automation for software releases (CI/CD).

• Deploy the SW system in-vehicle at a real race track, provide debugging support, and train UX researchers to operate the system independently during user studies.

• Contribute to documentation and information exchange among engineering and research teams.

• Review and guide others in writing clean and maintainable code.

• Manage the overall timeline for system development delivery and work closely with technical program manager to ensure milestones are achieved.

• Work on-site at our Los Altos office and travel monthly to a race track for vehicle testing.

Qualifications

• Master’s degree in Computer Science, or related field, with 5+ years of industry experience.

• Deep understanding of C++ and Python toolchains.

• Deep understanding and hands on experience with ROS2 framework.

• Strong understanding of Linux-based development, containerization (e.g., Docker), and system-level debugging tools.

• Consistent track record to navigate and integrate large codebases and research prototypes into complex systems.

• Demonstrated experience owning and delivering sophisticated applications or subsystems in production-like environments.

• Experience with UI development, including web-based interfaces or using game engines (e.g., Unity, Unreal Engine).

• Ability to design, deploy, and manage systems in cloud environments (e.g., AWS, GCP, Azure).

• Ability to communicate complex concepts clearly across different audiences.

• Have a high level of initiative and self-motivation, work without direct supervision.

Location USA, CA, Sunnyvale USA, WA, Bellevue

Description As a Principal Scientist within the Artificial General Intelligence (AGI) organization, you are a trusted part of the technical leadership. You bring business and industry context to science and technology decisions.

You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. You solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization.

You are a hands-on scientific leader. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.

You amplify your impact by leading scientific reviews within your organization or at your location. You scrutinize and review experimental design, modeling, verification and other research procedures. You probe assumptions, illuminate pitfalls, and foster shared understanding. You align teams toward coherent strategies. You educate, keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends.

You help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads.

You will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences.

San Diego preferred

Qualcomm's Multimedia R&D and Standards Group is seeking a candidate for the position of Video Compression Research Engineer with a focus on machine learning for video compression. You join a world-renowned team of video compression experts who develop algorithms, hardware architectures, and systems for state-of-the-art applications of classical and machine learning methods in video compression, video processing, point cloud coding and processing, AR/VR and computer vision use cases.

The ideal candidate will be a highly self-directed individual with strong creative and analytic skills, and a passion for machine learning and video compression technologies. Your work will involve developing innovative applications of Neural Networks in video compression to enhance state-of-the-art video codecs. This role offers the opportunity to contribute to groundbreaking advancements in video compression technology, working alongside a team of experts in a dynamic and collaborative environment.

We are considering candidates with various levels of experience. We are flexible on location and open to hiring anywhere, with preferred locations in USA, Germany and Taiwan.

Responsibilities: - Contribute to the conception, development, implementation, and optimization of new Neural Networks based algorithms allowing improved video compression. - Represent Qualcomm in the related standardization forums: JVET, MPEG Video, and ITU-T/VCEG. - Document and present new algorithms and implementations in various forms, including standards contributions, patent applications, conference papers and presentations, and journal publications, etc. - Ideal candidate would have the skills/experience below: - Knowledge of Neural Networks based data compression, and the theory, algorithms, and techniques used in video and image coding. - Experience in video compression standards, such as VVC/H.266 or HEVC/H.265, is a significant benefit. - Track record of successful research accomplishments demonstrated through published papers at leading conferences, and/or patent applications in the field of applications of Machine - Learning to image or video compression. - Excellent programming skills including Python and C/C++ combined with knowledge of at least one machine learning framework such as PyTorch. - Strong written and verbal English communication skills, great work ethic, and ability to work in a team environment to accomplish common goals. - PhD degree with relevant work experience or publications in the areas of video compression, video/image processing algorithms, or machine learning.

Qualifications: PhD or Masters degree in Electrical Engineering, Computer Science, Physics, Mathematics, or similar fields. 1+ years of experience with programming language such as C, C++, MATLAB, etc.

Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, Mathematics, Physics or related field and 4+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, Mathematics, Physics or related field and 3+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience. OR PhD in Engineering, Information Systems, Computer Science, Mathematics, Physics or related field and 2+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.

For other positions and to register please see: https://qualcomm.eightfold.ai/events/candidate/landing?plannedEventId=bkyZbLR19

Reader (Assistant/Associate Professor)
The Department of Computer Science at the University of Bath invites applications for up to seven faculty positions at various ranks from candidates who are passionate about research and teaching in artificial intelligence and machine learning. These are permanent positions with no tenure process. The start date is flexible.

The University of Bath is based on an attractive, single-site campus that facilitates interdisciplinary research. It is located on the edge of the World Heritage City of Bath and offers the lifestyle advantages of working and living in one of the most beautiful areas in the United Kingdom.

For more information and to apply, please visit: https://www.bath.ac.uk/campaigns/join-the-department-of-computer-science/

Project Summary:

Positron Emission Tomography (PET) is vital for diagnosing diseases like cancer, heart conditions, and neurological disorders. However, conventional PET/CT imaging exposes patients to radiation from tracers and CT scans. This Swiss National Science Foundation (SNSF)-funded project aims to address these challenges by creating data-driven models to enable high-quality, low-dose PET imaging, reducing radiation risks and enhancing accessibility without compromising diagnostic accuracy. This position focus on three main streams: - Denoising of Low-Dose PET Images: Developing models to reduce noise and enhance the quality of PET scans acquired at lower radiation doses. - CT-Free Attenuation Correction: Developing AI-driven techniques for PET imaging that eliminate the need for CT scans, reducing radiation exposure and associated costs. - Robust Image Reconstruction and Synthesis: Using deep learning to create high-quality PET and CT images from low-dose PET data to support accurate, non-invasive diagnostics. This work aims to advance personalized, non-invasive diagnostic techniques, making PET imaging safer and more accessible in clinical practice.

Position Details:

We are seeking a highly motivated PhD candidate to join our team in Switzerland, bringing a strong background in deep learning and a passion for medical imaging. The PhD candidate will play a central role in developing robust and generalizable AI methods to address key technical challenges in PET image reconstruction.

Key responsibilities include:

• Design and implement advanced denoising models for low-dose PET images, focusing on noise reduction while preserving diagnostic detail.
• Develop and validate CT-free attenuation correction techniques that enhance PET imaging without additional radiation exposure.
• Collaborate closely with interdisciplinary teams at the University of Cambridge, Tsinghua University, Lucerne University of Applied Sciences, and Luzerner Kantonsspital to integrate AI solutions into clinical practice.
• Contribute to top scientific publications and outreach activities.
• The project offers access to high-quality medical imaging datasets, a collaborative research environment, and guidance from academic and clinical experts in medical imaging and AI. The selected candidate will be employed for 48 months on the project.

Candidate Requirements:

• Master’s degree in Computer Science, Biomedical Engineering, or a related discipline.
• Strong background in deep learning with practical experience in medical imaging applications preferred.
• Proficiency in Python and machine learning frameworks such as PyTorch or TensorFlow.
• Excellent communication skills in English and an ability to work within international, multidisciplinary teams.
• An eagerness to contribute to impactful research in the field of medical diagnostics.

Benefits:

• Fully funded by the Swiss National Science Foundation (SNSF).
• The opportunity to work within an international research network and to contribute to the development of life-saving imaging technologies.
• Access to state-of-the-art datasets, resources, and facilities, fostering your growth in a supportive and collaborative environment.

Application Process:

Please submit your CV, a cover letter detailing your research experience and motivation, and contact information for two academic references. Applications will be reviewed on a rolling basis until the position is filled.

Contact Information:

For inquiries or to submit your application, please contact: Angelica Aviles-Rivero (aviles-rivero@tsinghua.edu.cn) and Javier Montoya (javier.montoya@hslu.ch)

Cambridge, MA

At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team in Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics.

The Team

The Human Aware Interactions and Learning team uses approaches from machine learning, robotics, and computer vision, along with insights from human factors literature, to devise new techniques that improve on the state of the art towards better machine understanding, prediction, and interactions with people in the driving domain, both in and around the vehicle.

We work with computational and cognitive researchers to test our approaches from a variety of data sources and human-in-the-loop experiments to devise ML approaches that work with the driver.

The Opportunity

We are seeking a Research Scientist to lead groundbreaking research at the intersection of machine learning, computer vision, and human factors. This role focuses on understanding, detecting, and developing intervention strategies for driver impairments, such as cognitive distraction and intoxication. The ideal candidate will contribute to fundamental research, publish in top-tier venues, and build machine learning models and prototypes that integrate human-in-the-loop data towards novel approaches for understanding and assisting drivers under diverse situations.

This is an opportunity to work on innovative research in human-robot interaction and intelligent vehicle systems in a collaborative and interdisciplinary team of experts in robotics, AI, and human factors. You will have access to innovative robotic platforms and simulation tools with the potential to contribute to academic publications and impactful real-world applications.

Responsibilities

• Conduct original research on driver impairment detection and intervention (e.g. warning, coaching, actuation) using machine learning and computer vision.

• Develop algorithms and models to analyze driver behavior, physiological signals, and other multimodal inputs, as well as perform ML-based interactions with the driver.

• Design, implement, and conduct human-in-the-loop behavioral studies, ensuring robustness and real-world applicability.

• Publish findings in high-impact conferences and journals.

• Collaborate with interdisciplinary teams, including human factors experts, cognitive scientists, and engineers.

• Prototype and validate ML-based intervention strategies to enhance driver safety and performance.

Qualifications

• PhD in Computer Vision, Machine Learning, Human-Centered AI, or a related field.

• Research experience in human and machine vision, behavior analysis, or multimodal learning.

• Strong publication record (e.g., CVPR, NeurIPS, ICCV, ICLR).

• Experience working with human-in-the-loop data: data collection, annotation strategies, and model training.

• Proficiency in deep learning frameworks (e.g., PyTorch, Jax, Hugginface) and data analysis tools.

• Ability to work both independently and as part of an interdisciplinary team.

Bonus Qualifications

• Experience in developing real-time AI systems for human monitoring.

• Familiarity with physiological and cognitive state estimation (e.g., eye tracking, EEG, heart rate variability).

• Background in human factors, cognitive psychology, or related fields.

• Experience deploying machine learning models in real-world environments.

• Knowledge of software development industry practices (version control, CI/CD, documentation).

Please submit a brief cover letter and add a link to Google Scholar to include a full list of publications when submitting your CV for this position.

Location

First and most importantly: our mission is to bring transparency and clarity to the world's data.

Our platform, FiftyOne, is where AI work happens. Our enterprise platform is the mission critical linchpin for managing unstructured data, model development, and AI systems at the world's largest companies, including dozens from the Fortune 500.

We believe that open source is the way to lead the data-centric AI revolution. Our open source version has 3 million downloads to-date.

Our software massively impacts AI work across almost every vertical: from self-driving cars to medical imaging to revolutionizing agriculture, we are at the thrilling center of real-world AI advancement’s next wave.

And we’re built on three key tenets:

• We are all human beings: we strive to be a “human-first” organization and treat everyone with the respect, care, and flexibility that all people deserve. 
• We are distributed: we believe in getting autonomy and power into the hands of people actually doing the work.
• We believe in the power of community.

Our fully distributed team is located across North America today.

About your role

As a Machine Learning Engineer here at Voxel51, you’ll collaborate with a team that delivers innovative features to support dataset curation, model analysis, and integrations that span the entire machine learning lifecycle, with a current emphasis on Visual AI. You’ll build powerful and extensible methods that users interact with via both API and no-code workflows, and you’ll solve unique challenges that arise when working with unstructured data (images,video, point-clouds, and meshes). Additionally, you will have the opportunity to contribute to a thriving open source community while also emphasizing enterprise-grade engineering for our commercial products.

Every member of our fully-remote team is empowered to own their work and play an active role in advancing our mission to democratize data-centric ML.

What you will do

• Push the boundaries of open-source data-centric AI with an emphasis on innovating new capabilities for our users to effectively work with unstructured datasets and building state of the models
• Scale data-centric AI approaches for the world’s largest enterprises to world scale, with billions of samples across continually learning models
• Work with UX designers and core software engineers to bring these state-of-the-art AI capabilities to life in production software ecosystems
• Play an active role in the discussion to inform company technical strategy as we build the software refinery that brings transparency and clarity to the world’s data

What you should bring

• 3+ years of professional software engineering experience developing ML products and software systems
• BS or MS in computer science or a related field
• Expertise with Python and a passion for elegant software
• Expertise with machine learning and scientific computing libraries (PyTorch, NumPy)
• Familiarity with NoSQL databases (MongoDB, DocumentDB, Elasticsearch)
• Experience maintaining or contributing to open source projects (or the passion to start!)
• Ability to work in a remote-first, cooperative environment using collaborative development tools (GitHub, Slack)
• Initiative and radical candor to constructively collaborate with your new teammates and our large user-base

The cash compensation for this person is in the $180K - $240K range. In addition to base comp for this role, we offer equity in the form of options, a variety of benefits, and the opportunity to grow in an exciting and collaborative environment.

Los Altos, CA

At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team in Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics.

The Mission

Make general-purpose robots a reality via large-scale embodied AI.

The Challenge

We envision a future where robots assist with household chores and cooking, aid the elderly in maintaining their independence, and enable people to spend more time on the activities they enjoy most. To achieve this, robots need to be able to operate reliably in messy, unstructured environments. Our mission is to answer the question “What will it take to create truly general-purpose robots that can accomplish a wide variety of tasks in settings like human homes with minimal human supervision?”. To answer this, we are gathering large datasets of physical interaction from a variety of sources (including robots and people) and training large generative foundation models on this physical interaction data along with language, video, audio, and other rich modalities.

The Team

Our goal is to revolutionize the field of robotic manipulation, enabling long-horizon dexterous behaviors to be efficiently instructed, learned, and improved over time in real world environments. Our team has deep cross-functional expertise across simulation, perception, controls, language, vision, multimodal learning, and generative modeling. Success is measured by the advancement of robot capabilities. Our north star is fundamental technological advancement in building robots that can flexibly perform a wide variety of tasks in diverse environments with minimal human supervision. Come join us and let’s make general-purpose robots a reality. We operate a fleet of robots, and robot-embodied teaching and deployment are key parts of our strategy. Some of our previous work is highlighted here.

The Opportunity

We’re looking for a driven Robotics Engineer who has experience developing and deploying robotic systems.

Responsibilities

• Contribute to the design and deployment of novel robotic systems through software development.

• Develop tooling to enable stable, performant, and scalable robotic platform deployments.

• Enable research into robot foundation models by working with mechanical/electrical engineers, technicians, and researchers to integrate, test, and deploy new sensors.

• Design and integrate creative system solutions; combining actuation, structure, and sensing, as well as mechanisms and sensory for human-scale manipulation.

• Improve on software/hardware systems and tooling toward more detailed operation of robots.