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CVPR 2024 Career Website

Here we highlight career opportunities submitted by our Exhibitors, and other top industry, academic, and non-profit leaders. We would like to thank each of our exhibitors for supporting CVPR 2024. Opportunities can be sorted by job category, location, and filtered by any other field using the search box. For information on how to post an opportunity, please visit the help page, linked in the navigation bar above.

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About the role You will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on creating highly realistic, emotional and life-like Synthetic humans through text-to-video. Within the team you’ll have the opportunity to work with different research teams and squads across multiple areas led by our Director of Science, Prof. Vittorio Ferrari, and directly impact our solutions that are used worldwide by over 55,000 businesses.

If you have seen the full ML lifecycle from ideation through implementation, testing and release, and you have a passion for large data, large model training and building solutions with clean code, this is your chance. This is an opportunity to work for a company that is impacting businesses at a rapid pace across the globe.


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B GARAGE was founded in 2017 by two PhD graduates from Stanford University. After having spent over five years researching robotics, computer vision, aeronautics, and drone autonomy, the co-founders set their minds on building a future where aerial robots would become an integral part of our daily lives without anyone necessarily piloting them. Together, our common goal is to redefine the user experience of drones and to expand the horizon for the use of drones.

The B GARAGE team is always looking for an enthusiastic, proactive, and collaborative Robotics and Automation Engineers to support the launch of intelligent aerial robots and autonomously sustainable ecosystems.

If you're interested in joining the B Garage team but don't see a role open that fits your background, apply to the general application and we'll reach out to discuss your career goals.


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Location San Diego


Description

Qualcomm AI Research is looking for world-class algorithm engineers in general domain machine learning, especially deep learning, generative AI, LLM, LVM. Come join a high-caliber team of engineers building advanced machine learning technology, best-in-class solutions, and user friendly model optimization tools such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit (https://github.com/quic/aimet) to enable state-of-the-art networks to run on devices with limited power, memory, and computation.

Members of our team enjoy the opportunity to participate in cutting edge research while simultaneously contributing technology that will be deployed worldwide in our industry-leading devices. You will be part of a multi-disciplinary talented team working on on-device generative AI optimization. Collaborate in a cross-functional environment spanning hardware, software and systems. See your design in action on industry-leading chips embedded in the next generation of smartphones, autonomous vehicles, robotics, and IOT devices.

Minimum Qualifications: • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.The R&D work responsibility for this position focuses on the following: Algorithms research and development in the area of Generative AI, LVM, LLM, Multi-modality Efficient inference algorithms research and development, e.g. batching, KV caching, efficient attentions, long context, speculative decoding Advanced quantization algorithms research and development for complex generative models, e.g., gradient/non-gradient based optimization, equivalent/non-equivalent transformation, automatic mixed precision, hardware in loop Model compression, lossy or lossless, structural and neural search Optimization based learning and learning based optimization Generative AI system prototyping Apply solutions toward system innovations for model efficiency advancement on device as well as in the cloud Python, Pytorch programmer Preferred Qualifications: Master's degree in Computer Science, Engineering, Information Systems, or related field. PHD's degree is preferred. 2+ years of experience with Machine Learning algorithms or systems engineering or related work experience


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Captions is the AI-powered creative studio. Millions of creators around the world have used Captions to make their video content stand out from the pack and we're on a mission to empower the next billion.

Based in NYC, we are a team of ambitious, experienced, and devoted engineers, designers, and marketers. You'll be joining an early team where you'll have an outsized impact on both the product and company's culture.

We’re very fortunate to have some the best investors and entrepreneurs backing us, including Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, Uncommon Projects, Kevin Systrom, Mike Krieger, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, Lenny Rachitsky, and more.

Check out our latest milestone and our recent feature on the TODAY show and the New York Times.

** Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) **

Responsibilities:

Conduct research and develop models to advance the state-of-the-art in generative video technologies, focusing on areas such as video in-painting, super resolution, text-to-video conversion, background removal, and neural background rendering.

Design and develop advanced neural network models tailored for generative video applications, exploring innovative techniques to manipulate and enhance video content for storytelling purposes.

Explore new areas and techniques to enhance video storytelling, including research into novel generative approaches and their applications in video production and editing.

Create tools and systems that leverage machine learning, artificial intelligence, and computational techniques to generate, manipulate, and enhance video content, with a focus on usability and scalability.

Preferred Qualifications:

PhD in computer science or related field or 3+ years of industry experience.

Publication Record: Highly relevant publication history, with a focus on generative video techniques and applications. Ideal candidates will have served as the primary author on these publications.

Video Processing Skills: Strong understanding of video processing techniques, including video compression, motion estimation, and object tracking, with the ability to apply these techniques in generative video applications.

Expertise in Deep Learning: Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar, with hands-on experience in designing, training, and deploying neural networks for video-related tasks.

Strong understanding of Computer Science fundamentals (algorithms and data structures).

Benefits: Comprehensive medical, dental, and vision plans

Anything you need to do your best work

We’ve done team off-sites to places like Paris, London, Park City, Los Angeles, Upstate NY, and Nashville with more planned in the future.

Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Please note benefits apply to full time employees only.


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The Perception team at Zoox is responsible for developing the eyes and ears of our self driving car. Navigating safely and competently in the world requires us to detect, classify, track and understand several different attributes of all the objects around us that we might interact with, all in real time and with very high precision.

As a member of the Perception team at Zoox, you will be responsible for developing and improving state of the art machine learning techniques for doing everything from 2D/3D object detection, panoptic segmentation, tracking, to attribute classification. You will be working not just with our team of talented engineers and researchers in perception, but cross functionally with several teams including sensors, prediction and planning, and you will have access to the best sensor data in the world and an incredible infrastructure for testing and validating your algorithms.


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The Prediction & Behavior ML team is responsible for developing machine-learned models that understand the full scene around our vehicle and forecast the behavior for other agents, our own vehicle’s actions, and for offline applications. To solve these problems we develop deep learning algorithms that can learn behaviors from data and apply them on-vehicle to influence our vehicle’s driving behavior and offline to provide learned models to autonomy simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team necessarily works very closely with the Planner team in the advancement of our overall vehicle behavior. The Prediction & Behavior ML team also works closely with our Perception, Simulation, and Systems Engineering teams on many cross-team initiatives.


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※Location※ South Korea, Uiwang


※Description※ 1) AI Perception - RGB image based object/scene reconstruction (Nerf, GS, LRM) - Object detection / analysi - Image-Text multimodal model

2) Manipulation Vision - Development of vision-based Bimanual Manipulation using deep learning technology

3) On-Device AI - Development of lightweight deep learning model and on-device AI optimization technology

4) Mobile robot SLAM- Development of algorithms for Perception, SLAM, Motion control and Path planning


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A postdoctoral position is available in Harvard Ophthalmology Artificial Intelligence (AI) Lab (https://ophai.hms.harvard.edu) under the supervision of Dr. Mengyu Wang (https://ophai.hms.harvard.edu/team/dr-wang/) at Schepens Eye Research Institute of Massachusetts Eye and Ear and Harvard Medical School. The start date is flexible, with a preference for candidates capable of starting in August or September 2024. The initial appointment will be for one year with the possibility of extension. Review of applications will begin immediately and will continue until the position is filled. Salary for the postdoctoral fellow will follow the NIH guideline commensurate with years of postdoctoral research experience.

In the course of this interdisciplinary project, the postdoc will collaborate with a team of world-class scientists and clinicians with backgrounds in visual psychophysics, engineering, biostatistics, computer science, and ophthalmology. The postdoc will work on developing statistical and machine learning models to improve the diagnosis and prognosis of common eye diseases such as glaucoma, age-related macular degeneration, and diabetic retinopathy. The postdoc will have access to abundant resources for education, career development and research both from the Harvard hospital campus and Harvard University campus. More than half of our postdocs secured a faculty position after their time in our lab.

For our data resources, we have about 3 million 2D fundus photos and more than 1 million 3D optical coherence tomography scans. Please check http://ophai.hms.harvard.edu/data for more details. For our GPU resources, we have 22 in-house GPUs in total including 8 80-GB Nvidia H100 GPUs, 10 48-GB Nvidia RTX A6000 GPUs, and 4 Nvidia RTX 6000 GPUs. Please check http://ophai.hms.harvard.edu/computing for more details. Our recent research has been published in ICCV 2023, ICLR 2024, CVPR 2024, IEEE Transactions on Medical Imaging, and Medical Image Analysis. Please check https://github.com/Harvard-Ophthalmology-AI-Lab for more details.

The successful applicant will:

  1. possess or be on track to complete a PhD or MD with background in computer science, mathematics, computational science, statistics, machine learning, deep learning, computer vision, image processing, biomedical engineering, bioinformatics, visual science and ophthalmology or a related field. Fluency in written and spoken English is essential.

  2. have strong programming skills (Python, R, MATLAB, C++, etc.) and in-depth understanding of statistics and machine learning. Experience with Linux clusters is a plus.

  3. have a strong and productive publication record.

  4. have a strong work ethic and time management skills along with the ability to work independently and within a multidisciplinary team as required.

Your application should include:

  1. curriculum vitae

  2. statement of past research accomplishments, career goal and how this position will help you achieve your goals

  3. Two representative publications

  4. contact information for three references

The application should be sent to Mengyu Wang via email (mengyu_wang at meei.harvard.edu) with subject “Postdoctoral Application in Harvard Ophthalmology AI Lab".


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Location Multiple Locations


Description

Members of our team are part of a multi-disciplinary core research group within Qualcomm which spans software, hardware, and systems. Our members contribute technology deployed worldwide by partnering with our business teams across mobile, compute, automotive, cloud, and IOT. We also perform and publish state-of-the-art research on a wide range of topics in machine-learning, ranging from general theory to techniques that enable deployment on resource-constrained devices. Our research team has demonstrated first-in-the-world research and proof-of-concepts in areas such model efficiency, neural video codecs, video semantic segmentation, federated learning, and wireless RF sensing (https://www.qualcomm.com/ai-research), has won major research competitions such as the visual wake word challenge, and converted leading research into best-in-class user-friendly tools such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit (https://github.com/quic/aimet). We recently demonstrated the feasibility of running a foundation model (Stable Diffusion) with >1 billion parameters on an Android phone under one second after performing our full-stack AI optimizations on the model.

Role responsibility can include both, applied and fundamental research in the field of machine learning with development focus in one or many of the following areas:

  • Conducts fundamental machine learning research to create new models or new training methods in various technology areas, e.g. large language models, deep generative models (VAE, Normalizing-Flow, ARM, etc), Bayesian deep learning, equivariant CNNs, adversarial learning, diffusion models, active learning, Bayesian optimizations, unsupervised learning, and ML combinatorial optimization using tools like graph neural networks, learned message-passing heuristics, and reinforcement learning.

  • Drives systems innovations for model efficiency advancement on device as well as in the cloud. This includes auto-ML methods (model-based, sampling based, back-propagation based) for model compression, quantization, architecture search, and kernel/graph compiler/scheduling with or without systems-hardware co-design.

  • Performs advanced platform research to enable new machine learning compute paradigms, e.g., compute in memory, on-device learning/training, edge-cloud distributed/federated learning, causal and language-based reasoning.

  • Creates new machine learning models for advanced use cases that achieve state-of-the-art performance and beyond. The use cases can broadly include computer vision, audio, speech, NLP, image, video, power management, wireless, graphics, and chip design

  • Design, develop & test software for machine learning frameworks that optimize models to run efficiently on edge devices. Candidate is expected to have strong interest and deep passion on making leading-edge deep learning algorithms work on mobile/embedded platforms for the benefit of end users.

  • Research, design, develop, enhance, and implement different components of machine learning compiler for HW Accelerators.

  • Design, implement and train DL/RL algorithms in high-level languages/frameworks (PyTorch and TensorFlow).


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Inria (Grenoble), France


human-robot interaction, machine learning, computer vision, representation learning

We are looking for highly motivated students joining our team at INRIA. This project will take place in close collaboration between Inria team THOTH and the multidisciplinary institute in artificial intelligence (MIAI) in Grenoble

Topic: Human-robot systems are challenging because the actions of one agent can significantly influence the actions of others. Therefore, anticipating the partner's actions is crucial. By inferring beliefs, intentions, and desires, we can develop cooperative robots that learn to assist humans or other robots effectively. In this project we are in particular interested in estimating human intentions to enable collaborative tasks between humans and robots such as human-to-robot and robot-to-human handovers.

Contact pia.bideau@inria.fr The thesis will be jointly supervised by Pia Bideau (THOTH), Karteek Alahari (THOTH) and Xavier Alameda Pineda (RobotLearn).


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Excited to see you at CVPR! We’ll be at booth 1404. Come see us to talk more about roles.

Our team consists of people with diverse software and academic experiences. We work together towards one common goal: integrating the software, you'll help us build into hundreds of millions of vehicles.

As the MLE, you will collaborate with researchers to perform research operations using existing infrastructure. You will use your judgment in complex scenarios and help apply standard techniques to various technical problems. Specifically, you will:

  • Characterize neural network quality, failure modes, and edge cases based on research data
  • Maintain awareness of current trends in relevant areas of research and technology
  • Coordinate with researchers and accurately convey the status of experiments
  • Manage a large number of concurrent experiments and make accurate time estimates for deadlines
  • Review experimental results and suggest theoretical or process improvements for future iterations
  • Write technical reports indicating qualitative and quantitative results to external parties

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Zoox is looking for a software engineer to join our Perception team and help us build novel architectures for classifying and understanding the complex and dynamic environments in our cities. In this role, you will have access to the best sensor data in the world and an incredible infrastructure for testing and validating your algorithms. We are creating new algorithms for segmentation, tracking, classification, and high-level scene understanding, and you could work on any (or all!) of these components.

We're looking for engineers with advanced degrees and experience building perception pipelines that work with real data in rapidly changing and uncertain environments.


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Redmond, Washington, United States


Overview We are seeking skilled and passionate Senior Research Scientist to join our Responsible & Open Ai Research (ROAR) team in Azure Cognitive Services at Redmond, WA.

As a Senior Research Scientist, you will play a key role in advancing Responsible AI approaches to ensure safe releases of the rapidly evolving multimodal, AI models such as GPT-4 Vision, DALL-E, Sora, and beyond, as well as to expand and enhance the Azure AI Content Safety Service.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Responsibilities Conduct cutting-edge research to develop Responsible AI definitions, methodologies, algorithms, and models for both measurement and mitigation of multimodal AI risks. Stay abreast of the latest advancements in the field and contribute to the scientific community through publications at top venues. Enable the safe release of multimodal models from OpenAI in Azure OpenAI Service, expand and enhance the Azure AI Content Safety Service with new detection technologies. Develop innovative approaches to address AI safety challenges for diverse customer scenarios. Embody our Culture and Values


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Seattle, US


Our Company Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences. We’re passionate about empowering people to craft beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We’re on a mission to hire the very best and are committed to building exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

The Opportunity Photoshop ART is seeking a Research Scientist to join our inpainting R&D team focused on making significant progress in image generation/restoration, low level vision, image editing with an eventual posture toward productization. Individuals in this role are expected to be expert in identified research areas such as artificial intelligence, machine learning, computer vision, and image processing. The ideal candidate will have a keen interest in producing new science to advance Adobe products.

What you'll Do Work towards long-term results-oriented research goals, while identifying intermediate achievements. Contribute to research that can be applied to Adobe product development. Help integrating novel research work into Adobe’s product. Lead and collaborate on research projects across different Adobe divisions. What you need to succeed Ph.D. and solid publications in machine learning, AI, computer science, statistics, or scene semantic understanding. Experience communicating research for public audiences of peers. Experience working in teams. Knowledge in a programming language. Preferred Qualification 2 years of professional full-time experience preferred, but not required 2+ year(s) of internship with primary emphasis on AI research in image generation, low level vision, image restoration, and segmentation Experience in collaboration with a team with varied strengths. 4+ First-author publications at peer-reviewed AI conferences (e.g. NIPS, CVPR, ECCV, ICML, ICLR, ICCV, and ACL). Experience in developing and debugging in Python. At Adobe, you will be immersed in an exceptional work environment that is recognized throughout the world on Best Companies lists. You will also be surrounded by colleagues who are committed to helping each other grow through our unique Check-In approach where ongoing feedback flows freely.

If you’re looking to make an impact, Adobe's the place for you. Discover what our employees are saying about their career experiences on the Adobe Life blog and explore the meaningful benefits we offer.

Adobe is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, or veteran status.

Our compensation reflects the cost of labor across several  U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $129,400 -- $242,200 annually. Pay within this range varies by work location and may also depend on job-relate


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