※Location※ South Korea Seoul / Pangyo

※Description※ 1) Deep learning compression and optimization - Development of algorithms for compression and optimization of deep learning networks - Perform deep learning network embedding (requires understanding of HW platform)

2) AD vision recognition SW - Development of deep learning recognition technology based on sensors such as cameras - Development of pre- and post-processing algorithms and function output - Development of optimization of image recognition algorithm

3) AD decision/control SW - Development of information-based map generation technology recognized by many vehicles - Development of learning-based nearby object behavior prediction model - Development of driving mode determination and collision prevention function of Lv 3 autonomous driving system

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).

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 a Research Engineer, you will work collaboratively to improve our models and iterate on novel research directions, sometimes in just days. We're looking for talented engineers who would enjoy applying their skills to deeply complex and novel AI problems. Specifically, you will:

• Apply and extend the Helm proprietary algorithmic toolkit for unsupervised learning and perception problems at scale
• Carefully execute the development and maintenance of tools used for deep learning experiments designed to provide new functionality for customers or address relevant corner cases in the system as a whole
• Work closely with software and autonomous vehicle engineers to deploy algorithms on internal and customer vehicle platforms

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.

Location Madrid, ESP

Description At Amazon, we are committed to being the Earth’s most customer-centric company. The International Technology group (InTech) owns the enhancement and delivery of Amazon’s cutting-edge engineering to all the varied customers and cultures of the world. We do this through a combination of partnerships with other Amazon technical teams and our own innovative new projects.

You will be joining the Tools and Machine learning (Tamale) team. As part of InTech, Tamale strives to solve complex catalog quality problems using challenging machine learning and data analysis solutions. You will be exposed to cutting edge big data and machine learning technologies, along to all Amazon catalog technology stack, and you'll be part of a key effort to improve our customers experience by tackling and preventing defects in items in Amazon's catalog.

We are looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading machine learning solutions. We strongly value your hard work and obsession to solve complex problems on behalf of Amazon customers.

Location Madrid, ESP

Description Amazon's International Technology org in EU (EU INTech) is creating new ways for Amazon customers discovering Amazon catalog through new and innovative Customer experiences. Our vision is to provide the most relevant content and CX for their shopping mission. We are responsible for building the software and machine learning models to surface high quality and relevant content to the Amazon customers worldwide across the site.

The team, mainly located in Madrid Technical Hub, London and Luxembourg, comprises Software Developer and ML Engineers, Applied Scientists, Product Managers, Technical Product Managers and UX Designers who are experts on several areas of ranking, computer vision, recommendations systems, Search as well as CX. Are you interested on how the experiences that fuel Catalog and Search are built to scale to customers WW? Are interesting on how we use state of the art AI to generate and provide the most relevant content?

We are looking for Applied Scientists who are passionate to solve highly ambiguous and challenging problems at global scale. You will be responsible for major science challenges for our team, including working with text to image and image to text state of the art models to scale to enable new Customer Experiences WW. You will design, develop, deliver and support a variety of models in collaboration with a variety of roles and partner teams around the world. You will influence scientific direction and best practices and maintain quality on team deliverables.

Vancouver

Who we are Established in 2017, Wayve is a leader in autonomous vehicle technology, driven by breakthroughs in Embodied AI. Our intelligent, mapless, and hardware-agnostic technologies empower vehicles to navigate complex environments effortlessly.

Supported by prominent investors, Wayve is advancing the transition from assisted to fully automated driving, making transportation safer, more efficient, and universally accessible. Join our world-class, multinational team of engineers and researchers as we push the boundaries of frontier AI and autonomous driving, creating impactful technologies and products on a global scale

Where you will have an impact Science is the team that is advancing our end-to-end autonomous driving research. The team’s mission is to accelerate our journey to AV2.0 and ensure the future success of Wayve by incubating and investing in new ideas that have the potential to become game-changing technological advances for the company.

As the first Research Manager in our Vancouver office, you will be responsible for managing & scaling a strong Science team in collaboration with other Wayve science teams in London and Mountain View. You will provide coaching and guidance to each of the researchers and engineers within your team and work with leaders across the company to ensure sustainable career growth for your team during a period of growth in the company. You will participate in our project-based operating model where your focus will be unlocking the potential of your team and its technical leaders to drive industry-leading impact. As part of your work, you will help identify the right projects to invest in, ensure the right allocation of resources to those projects, keep the team in good health, provide technical feedback to your team, share progress to build momentum, and build alignment and strong collaboration across the wider Science organisation. We are actively hiring and aim to substantially grow our research team over the next two years and you will be at the heart of this.

Challenges you will own Work closely with team members to develop career plans and growth trajectories based on each individual’s strengths and weaknesses and their own aspirations. Work closely with project leads to ensure team members are having strong impact and are set up for success. Work closely with project leads and Science leadership to ensure projects are resourced in a way that balances the needs of the business with the needs of the individuals. Offer coaching and technical mentorship to direct reports (especially project leads). Bring technical & project management expertise and experience to help accelerate our progress and decision-making. Challenge the status quo (both technical and organisational/process). Prioritize effectively and keep processes lean and effective. Partner with leadership to maintain a culture of cross-boundary collaboration, impact, innovation, and health. Grow the team as a hiring manager, to bring in complementary, diverse skill sets and backgrounds. Anticipate the needs of the business 6-24 months out, identify areas where additional resources are needed or we need to grow new domain expertise, and pitch this to leadership for investment. Contribute to the day-to-day running of the Science team’s operations and larger collaborative efforts.

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 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 Seattle, WA Palo Alto, CA

Description Amazon’s product search engine is one of the most heavily used services in the world, indexes billions of products, and serves hundreds of millions of customers world-wide. We are working on an AI-first initiative to continue to improve the way we do search through the use of large scale next-generation deep learning techniques. Our goal is to make step function improvements in the use of advanced multi-modal deep-learning models on very large scale datasets, specifically through the use of advanced systems engineering and hardware accelerators. This is a rare opportunity to develop cutting edge Computer Vision and Deep Learning technologies and apply them to a problem of this magnitude. Some exciting questions that we expect to answer over the next few years include: * How can multi-modal inputs in deep-learning models help us deliver delightful shopping experiences to millions of Amazon customers? * Can combining multi-modal data and very large scale deep-learning models help us provide a step-function improvement to the overall model understanding and reasoning capabilities? We are looking for exceptional scientists who are passionate about innovation and impact, and want to work in a team with a startup culture within a larger organization.

Location San Diego

Description

Artificial Intelligence is changing the world for the benefit of human beings and societies. QUALCOMM, as the world's leading mobile computing platform provider, is committed to enable the wide deployment of intelligent solutions on all possible devices – like smart phones, autonomous vehicles, robotics and IOT devices. Qualcomm is creating building blocks for the intelligent edge.

We are part of Qualcomm AI Research, and we focus on advancing Edge AI machine learning technology – including model fine tuning, hardware acceleration, model quantization, model compression, network architecture search (NAS), edge inference and related fields. Come join us on this exciting journey. In this particular role, you will work in a dynamic research environment, be part of a multi-disciplinary team of researchers and software engineers who work with cutting edge AI frameworks and tools. You will architect, design, develop, test, and deploy on- and off-device benchmarking workflows for model zoos.

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 successful applicant should have a strong theoretical background and proven hands-on experience with AI as modern software-, web-, and cloud-engineering.

Must have experience and skills: Strong theoretical background in AI and general ML techniques Proven hands-on experience with model training, inference, and evaluation. Proven hands-on experience with PyTorch, ONNX, TensorFlow, CUDA, and others. Experience developing data pipelines for ML/AI training and inferencing in the cloud. Prior experience in deploying containerized (web-) applications to IAAS environments such as AWS (preferred), Azure or GCP, backed by Dev-Ops and CI/CD technologies. Strong Linux command line skills. Strong experience with Docker and Git. Strong general analytical and debugging skills. Prior experience working in agile environments. Prior experience in collaborating with multi-disciplinary teams across time zones. Strong team player, communicator, presenter, mentor, and teacher. Preferred extra experience and skills: Prior experience with model quantization, profiling and running models on edge devices. Prior experience in developing full stack web applications using frameworks such as Ruby-on-Rails (preferred), Django, Phoenix/Elixir, Spring, Node.js or others. Knowledge of relational database design and optimization, hands on experience with running Postgres (preferred), MySQL or other relational databases in production Preferred qualifications: Bachelor's, Master's and/or PhD degree in Computer Science, Engineering, Information Systems, or related field and 2-5 years of work experience in Software Engineering, Systems Engineering, Hardware Engineering or related.

London

Who are we?

Our team is the first in the world to use autonomous vehicles on public roads using end-to-end deep learning, computer vision and reinforcement learning. Leveraging our multi-national world-class team of researchers and engineers, we’re using data to learn more intelligent algorithms to bring autonomy for everyone, everywhere. We aim to be the future of self-driving cars, learning from experience and data.

Where you’ll have an impact

We are currently looking for people with research expertise in AI applied to autonomous driving or similar robotics or decision making domain, inclusive, but not limited to the following specific areas:

Foundation models for robotics Model-free and model-based reinforcement learning Offline reinforcement learning Large language models Planning with learned models, model predictive control and tree search Imitation learning, inverse reinforcement learning and causal inference Learned agent models: behavioral and physical models of cars, people, and other dynamic agents You'll be working on some of the world's hardest problems, and able to attack them in new ways. You'll be a key member of our diverse, cross-disciplinary team, helping teach our robots how to drive safely and comfortably in complex real-world environments. This encompasses many aspects of research across perception, prediction, planning, and control, including:

How to leverage our large, rich, and diverse sources of real-world driving data How to architect our models to best employ the latest advances in foundation models, transformers, world models, etc. Which learning algorithms to use (e.g. reinforcement learning, behavioural cloning) How to leverage simulation for controlled experimental insight, training data augmentation, and re-simulation How to scale models efficiently across data, model size, and compute, while maintaining efficient deployment on the car You also have the potential to contribute to academic publications for top-tier conferences like NeurIPS, CVPR, ICRA, ICLR, CoRL etc. working in a world-class team to achieve this.

What you’ll bring to Wayve

Thorough knowledge of and 5+ years applied experience in AI research, computer vision, deep learning, reinforcement learning or robotics Ability to deliver high quality code and familiarity with deep learning frameworks (Python and Pytorch preferred) Experience leading a research agenda aligned with larger goals Industrial and / or academic experience in deep learning, software engineering, automotive or robotics Experience working with training data, metrics, visualisation tools, and in-depth analysis of results Ability to understand, author and critique cutting-edge research papers Familiarity with code-reviewing, C++, Linux, Git is a plus PhD in a relevant area and / or track records of delivering value through machine learning are a big plus. What we offer you

Attractive compensation with salary and equity Immersion in a team of world-class researchers, engineers and entrepreneurs A unique position to shape the future of autonomy and tackle the biggest challenge of our time Bespoke learning and development opportunities Relocation support with visa sponsorship Flexible working hours - we trust you to do your job well, at times that suit you and your time Benefits such as an onsite chef, workplace nursery scheme, private health insurance, therapy, daily yoga, onsite bar, large social budgets, unlimited L&D requests, enhanced parental leave, and more!

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".

We are looking for a Research Engineer, with passion for working on cutting edge problems that can help us create highly realistic, emotional and life-like synthetic humans through text-to-video.

Our aim is to make video content creation available for all - not only to studio production!

🧑🏼‍🔬 You will be someone who loves to code and build working systems. You are used to working in a fast-paced start-up environment. You will have experience with the software development life cycle, from ideation through implementation, to testing and release. You will also have extensive knowledge and experience in Computer Vision domain. You will also have experience within Generative AI space (GANs, Diffusion models and the like!).

👩‍💼 You will join a group of more than 50 Engineers in the R&D department and will have the opportunity to collaborate with multiple research teams across diverse areas, our R&D research is guided by our co-founders - Prof. Lourdes Agapito and Prof. Matthias Niessner and director of Science Prof. Vittorio Ferrari.

If you know and love DALL.E, MUSE, IMAGEN, MAKE-A-VIDEO, STABLE DIFFUSION and more - and you love large data, large compute and writing clean code, then we would love to talk to you.

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 a Research Engineer for Optimization, you will focus on research and development related to the optimization of ML models on GPU’s or AI accelerators. You will use your judgment in complex scenarios and apply optimization techniques to a wide variety of technical problems. Specifically, you will:

• Research, prototype and evaluate state of the art model optimization techniques and algorithms
• Characterize neural network quality and performance based on research, experiment and performance data and profiling
• Incorporate optimizations and model development best practices into existing ML development lifecycle and workflow.
• Define the technical vision and roadmap for DL model optimizations
• Write technical reports indicating qualitative and quantitative results to colleagues and customers
• Develop, deploy and optimize deep learning (DL) models on various GPU and AI accelerator chipsets/platforms

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