The Autonomy Software Metrics team is responsible for providing engineers and leadership at Zoox with tools to evaluate the behavior of Zoox’s autonomy stack using simulation. The team collaborates with experts across the organization to ensure a high safety bar, great customer experience, and rapid feedback to developers. The metrics team is responsible for evaluating the complete end-to-end customer experience through simulation, evaluating factors that impact safety, comfort, legality, road citizenship, progress, and more. You’ll be part of a passionate team making transportation safer, smarter, and more sustainable. This role gives you high visibility within the company and is critical for successfully launching our autonomous driving software.

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.

※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

San Jose, CA

The Media Analytics team at NEC Labs America is seeking outstanding researchers with backgrounds in computer vision or machine learning. Candidates must possess an exceptional track record of original research and passion to create high impact products. Our key research areas include autonomous driving, open vocabulary perception, prediction and planning, simulation, neural rendering, agentic LLMs and foundational vision-language models. We have a strong internship program and active collaborations with academia. The Media Analytics team publishes extensively at top-tier venues such as CVPR, ICCV or ECCV.

To check out our latest work, please visit: https://www.nec-labs.com/research/media-analytics/

Qualifications: 1. PhD in Computer Science (or equivalent) 2. Strong publication record at top-tier computer vision or machine learning venues 3. Motivation to conduct independent research from conception to implementation.

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.

Location Multiple Locations

Description Today, more intelligence is moving to end devices, and mobile is becoming the pervasive AI platform. Building on the smartphone foundation and the scale of mobile, Qualcomm envisions making AI ubiquitous—expanding beyond mobile and powering other end devices, machines, vehicles, and things. We are inventing, developing, and commercializing power-efficient on-device AI, edge cloud AI, and 5G to make this a reality.

Job Purpose & Responsibilities As a member of Qualcomm’s ML Systems Team, you will participate in two activities: Development and evolution of ML/AI compilers (production and exploratory versions) for efficient mappings of ML/AI algorithms on existing and future HW Analysis of ML/AI algorithms and workloads to drive future features in Qualcomm’s ML HW/SW offerings

Key Responsibilities: Contributing to the development and evolution of ML/AI compilers within Qualcomm Defining and implementing algorithms for mapping ML/AI workloads to Qualcomm HW Understanding trends in ML network design, through customer engagements and latest academic research, and how this affects both SW and HW design Creation of performance-driven simulation components (using C++, Python) for analysis and design of high-performance HW/SW algorithms on future SoCs Exploration and analysis of performance/area/power trade-offs for future HW and SW ML algorithms Pre-Silicon prediction of performance for various ML algorithms Running, debugging and analyzing performance simulations to suggest enhancements to Qualcomm hardware and software to tackle compute and system memory-related bottlenecks · Successful applications will work in cross-site, cross-functional teams.

Requirements: Demonstrated ability to learn, think and adapt in fast changing environment Detail-oriented with strong problem-solving, analytical and debugging skills Strong communication skills (written and verbal) Strong background in algorithm development and performance analysis is essential The following experiences would be significant assets: Strong object-oriented design principles Strong knowledge of C++ Strong knowledge of Python Experience in compiler design and development Knowledge of network model formats/platforms (eg. Pytorch, Tensorflow, ONNX) is an asset. On-silicon debug skills of high-performance compute algorithms · Knowledge of algorithms and data structures Knowledge of software development processes (revision control, CD/CI, etc.) · Familiarity with tools such as git, Jenkins, Docker, clang/MSVC Knowledge of computer architecture, digital circuits and event-driven transactional models/simulators

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 computer vision technologies, with a focus on creating highly realistic digital faces, bodies, avatars.

Strive to set new standards in the realism of 3D digital human appearance, movement, and personality, ensuring that generated content closely resembles real-life scenarios.

Implement techniques to achieve high-quality results in zero-shot or few-shot settings, as well as customized avatars for different use cases while maintaining speed and accuracy.

Develop innovative solutions to enable comprehensive customization of video content, including the creation of digital people, modifying scenes, and manipulating actions and speech within videos.

Preferred Qualifications:

PhD in computer science (or related field) and/ or 5+ years of industry experience.

Strong academic background with a focus on computer vision and transformers, specializing in NeRFs, Gaussian Splatting, Diffusion, GANs or related areas.

Publication Record: Highly relevant publication history, with a focus on generating or manipulating realistic digital faces, bodies, expressions, body movements, etc. Ideal candidates will have served as the primary author on these publications.

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 multimodal 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.

Location Multiple Locations

Description

Qualcomm's Multimedia R&D and Standards Group is seeking candidates for Video Compression Research Engineer positions. You will be part of world-renowned team of video compression experts. The team develops 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 successful candidate for this position will be a highly self-directed individual with strong creative and analytic skills and a passion for video compression technology. You will work on, but not be limited to, developing new applications of classical and machine learning methods in video compression improving state-of-the-art video codecs.

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

Responsibilities: Contribute to the conception, development, implementation, and optimization of new algorithms extending existing techniques and systems allowing improved video compression. Initiate ideas, design and implement algorithms for superior hardware encoder performance, including perceptually based bit allocation. Develop new algorithms for deep learning-based video compression solutions. 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 and journal publications, presentations, etc. Ideal candidate would have the skills/experience below: Expert knowledge of the theory, algorithms, and techniques used in video and image coding. Knowledge and experience of video codecs and their test models, such as ECM, VVC, HEVC and AV1. Experience with deep learning structures CNN, RNN, autoencoder etc. and frameworks like TensorFlow/PyTorch. Track record of successful research accomplishments demonstrated through published papers, and/or patent applications in the fields of video coding or video processing. Solid programming and debugging skills in C/C++. Strong written and verbal English communication skills, great work ethic, and ability to work in a team environment to accomplish common goals. PhD or Masters degree in Electrical Engineering, Computer Science, Physics, Mathematics or similar field, or equivalent practical experience.

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.

Location Bellevue, WA

Description Are you excited about developing generative AI and foundation models to revolutionize automation, robotics and computer vision? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale.

This role is for the AFT AI team which has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Amazon Fulfillment Network. These solutions typically utilize machine learning and computer vision techniques, applied to text, sequences of events, images or video from existing or new hardware. The team is comprised of scientists, who develop machine learning and computer vision solutions, analytics, who evaluate the expected business impact for a project and the performance of these solutions, and software engineers, who provide necessary support such as annotation pipelines and machine learning library development.

We are looking for an Applied Scientist with expertise in computer vision. You will work alongside other CV scientists, engineers, product managers and various stakeholders to deploy vision models at scale across a diverse set of initiatives. If you are a self-motivated individual with a zeal for customer obsession and ownership, and are passionate about applying computer vision for real world problems - this is the team for you.

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.

About the role As a detail-oriented and experienced Data Annotation QA Coordinator you will be responsible for both annotating in-house data-sets and ensuring the quality assurance of our outsourced data annotation deliveries.Your key responsibilities will include text, audio, image, and video annotation tasks, following detailed guidelines. To be successful in the team you will have to be comfortable working with standard tools and workflows for data annotation and possess the ability to manage projects and requirements effectively.

You will join a group of more than 40 Researchers and Engineers in the R&D department. This is an open, collaborative and highly supportive environment. We are all working together to build something big - the future of synthetic media and programmable video through Generative AI. You will be a central part of a dynamic and vibrant team and culture.

Please, note, this role is office-based. You will be working at our modern friendly office at the very heart of London.

Vancouver, British Columbia, Canada

Overview Microsoft Research (MSR), a leading industrial research laboratory comprised of over 1,000 computer scientists working across the United States, United Kingdom, China, India, Canada, and the Netherlands.

We are currently seeking a Senior Researcher in the area of  Artificial Specialized Intelligence located in Vancouver, British Columbia, with a keen interest in developing cutting-edge large foundation models and post-training techniques for different domains and scenarios. This is an opportunity to drive an ambitious research agenda while collaborating with diverse teams to push for novel applications of those areas.  
  Over the past 30 years, our scientists have not only conducted world-class computer science research but also integrated advanced technologies into our products and services, positively impacting millions of lives and propelling Microsoft to the forefront of digital transformation.

Responsibilities Conduct cutting-edge research in large foundation models, focusing on applying large foundation models in specific domain. Collaborate with cross-functional teams to integrate solutions into Artificial Intelligence (AI) -driven system. Develop and maintain research prototypes and software tools, ensuring that they are well-documented and adhere to best practices in software development. Publish research findings in top-tier conferences and journals and present your work at industry events. Collaborate with other AI researchers and engineers, sharing knowledge and expertise to foster a culture of innovation and continuous learning within the team.

Location New York, NY Seattle, WA Boston, MA

Description Climate Pledge Friendly helps customers discover and shop for products that are more sustainable. We partner with trusted sustainability certifications to highlight products that meet strict standards and help preserve the natural world. By shifting customer demand towards more sustainable products, we incentivize selling partners to build better selection, creating a virtuous cycle that yields significant environmental benefit at scale.

We are seeking a Senior Applied Scientist who is not just adept in the theoretical aspects of Machine Learning (ML), Artificial Intelligence (AI), and Large Language Models (LLMs) but also possesses a pragmatic, hands-on approach to navigating the complexities of innovation. You will take the lead in conceptualizing, building, and launching models that significantly improve our shopping experience. A successful applicant will display a comprehensive skill set across machine learning model development, implementation, and optimization. This includes a strong foundation in data management, software engineering best practices, and a keen awareness of the latest developments in distributed systems technology.

You will work with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed ML models and services. The types of initiatives you can expect to work on include a) personalized recommendations that help our customers find the right sustainable products on each shopping journey, b) automated solutions that combine ML/LLM and data mining to identify products that align with our sustainability goals and resonate with our customers' values, and c) models to measure the environmental and econometric impacts of sustainable shopping.

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".